Oportunidades Públicas

Assembly and measurement of synthetic gene circuits

Construct DNAs using techniques from molecular biology and then measure their output in growing cell cultures.

Quantification of remodeling in patients with tetralogy of Fallot

1 in 2000 kids are born with tetralogy of Fallot, a combination of 4 serious congenital heart defects. To overcome these problems, the patient undergoes a series of surgeries and the heart responds by remodeling, adapting its form and function. However, the way this adaptation occurs is not fully characterized. The goal of this study is to locally quantify the remodeling of the heart in response to these surgeries. We will magnetic resonance images and the finite element method. This research will enable the development of predictive models to help the planning and optimization of the current surgeries.

Size and scale of volcanoes in different environments of the cortex

This project will use data from a database data of morphometry of volcanoes (i.e., Grosse et al., 2008) to understand the distribution of the size and scale of the volcanoes. The student will perform statistical analysis and thermodynamic

Deep learning based super resolution reconstruction for high resolution coronary magnetic resonance angiography

Coronary artery disease is currently diagnosed with X-ray or computed tomography coronary angiography (CTCA). However, both modalities expose patients to ionising radiation and iodinated contrast agents (CA). We have developed an alternative approach, coronary magnetic resonance angiography (CMRA), which is non-invasive, does not require the injection of CA and is free of radiation. Our 3D CMRA technique is approaching the resolution of CTCA but still requires a 10-minute scan. To further shorten the scan time to <1 minute and match the resolution of CTCA (0.6mm3), we propose to investigate novel deep learning based super resolution (SR) image reconstruction networks. The work will include a systematic literature review and the implementation of the most promising SR networks. We have a large clinical dataset of CMRA/CTCA data that can be used for training, testing and validation. It would be useful to know about the fundamentals of artificial intelligence.

Acquisition, reconstruction and motion correction for 3D whole-heart Magnetic Resonance Imaging

Magnetic Resonance Imaging (MRI) is an important non-invasive tool for risk assessment and treatment monitoring of cardiovascular disease. In comparison to other imaging modalities (ultrasound, x-ray and computed tomography) MRI has the advantage of combining excellent soft tissue contrast with high spatial resolution. However, a major limitation of current MRI protocols is that all imaging sequences are acquired sequentially, with different resolution, geometric orientations and breath-hold positions, resulting in long planning and scan times. Moreover, image quality degradation due to respiratory and cardiac motion are major challenges that greatly affect the accuracy and reproducibility of cardiac MRI. This research includes the development of novel whole-heart 3D MRI sequences, motion compensation techniques and deep learning methods to enable 3D, easy-to-plan, fast and efficient quantitative multi-parametric MRI of heart and vessels. The research is done together with King’s College London. Basic knowledge of MRI, signal processing and artificial intelligence would be useful.

Memory and knowledge: mapping civic knowledge to improve hydrological and hydrogeological knowledge

Compile the community's knowledge about the hydrological state and its evolution over time (perennial and intermittent rivers, water outcrops).
Map this knowledge in GIS tools (QGIS, Google Earth)
Site study: Parque Nacional del Río Clarillo (RM)

Bioremediation

Development of biological systems for the treatment of contaminants.

CO2 Emissions quotas in the Climate Change Framework Law

La Ley 21455 - Ley Marco de Camblio Climatico - Art. 5(b) define “ Presupuestos sectoriales de emisiones de gases de efecto invernadero al año 2030 asignados a los sectores señalados en el artículo 8°, de acuerdo a criterios de costo efectividad y equidad.” Esto se logra a traves de normas de emision para cada sector.
Esta investigacion indaga en como aterrizar estos conceptos considerando los dos criterios, y cuanto pueden cambiar los presupuestos segun qué criterio se considere.

Asignar los presupuestos es vital para que cada sector defina sus esfuerzos de mitigacion. El resultado de la investigacion puede ayudar a la politica publica. Ideal que hayan cursado ICS3742. (esta oportunidad se ofrece en 5 o 10 créditos)

Optimizing Bacterial Self-Healing in Concrete: Encapsulation vs. Direct Addition for Enhanced Performance

This research explores the innovative autonomous self-healing approach in concrete, which incorporates bacteria to enable self-repair of cracks. The focus is on evaluating two primary methods: direct addition of bacteria to the concrete mixture and encapsulation of bacteria within microcapsules.

In the direct addition method, bacteria and nutrients such as calcium lactate are embedded into the concrete. When cracks form and water seeps in, the bacteria activate and convert nutrients into calcium carbonate (CaCO₃), effectively sealing the cracks. The encapsulation method, on the other hand, uses microcapsules containing bacteria, which rupture upon crack formation to release healing agents that repair the damage.

This research explores the innovative use of bacteria for autonomous self-healing in concrete. It evaluates two main methods: direct addition of bacteria to the concrete mix and encapsulation in microcapsules.

Direct addition activates bacteria upon water ingress to produce calcium carbonate (CaCO₃) and seal cracks, while encapsulation releases repair agents when microcaps

Monitoring Seismicity in Front of the Juan Fernández Ridge

Chrono-Nutrition: A Study on Biological Rhythms and Eating Patterns

Recent research highlights the importance of chrono-nutrition, which studies how the timing of food intake affects health and performance. However, understanding these effects can be challenging due to the complexity of interactions between the internal biological clock and eating habits. With this in mind, we are looking for students interested in learning and applying mathematical modeling tools to develop a predictive system for chrono-nutrition. Participants will collect chronobiology and nutrition data to build mathematical models capable of predicting the effects of chrono-nutrition on health and performance.

Exploring environmental data for observing salt intrusion in rivers and estuaries

Construction of a preliminary geological map in remote areas

This Ipre aims to provide students with the methodology for generating a preliminary geological map based on collecting and integrating existing information and acquiring new information from satellite imagery for remote or difficult-to-access areas. A high-resolution Digital Elevation Model (DEM) will be constructed, and photogeological and geomorphological mapping will be carried out. The case study will be the North Patagonian Batholith in the Aysén region, at the plate triple junction of the Taitao Peninsula.

Audio to text using Natural Language Processing

The objective of this research is to program software that implements state-of-the-art Natural Language Processing (NLP) models for real-time audio-to-text translation. Models based on deep neural networks and Transformers are considered.

Advanced programming knowledge is required, but a background in NLP and application development is desirable. Weekly meetings will be held to monitor progress.

Video to text using Computer Vision and Natural Language Processing

The objective of this research is to program software that implements state-of-the-art computer vision models for pose estimation and translates them into text using Natural Language Processing (NLP) in real time. Models based on deep neural networks and Transformers are considered.

Advanced programming knowledge is required, but a background in computer vision, NLP, and application development is desirable. Weekly meetings will be held to monitor progress.

Modelling water transport in porous soils

Part of Carlos Faúndez Fondecyt de Iniciación Proyect: Field-scale estimation of macropore parameters for dual permeability models: An integrative approach incorporating pore-scale modeling and applied geophysics.

1. Implement a unsteady 1-D model for the transport of volumetric water content and hydraulic head in a heterogeneous soil column.

2. Analyse the effect of the non-linearity induced by the dependence of the soil hydraulic conductivity on the quantities transported.

3. Extend 1-D model to a 2-D unsteady model with azimuthal symmetry.

* The development of the model will be in Python on Julia. However, the final version of this model must translated to R. The co-supervisor Carlos Faúndez from Ing. Hidráulica y Ambiental will guide and support the translation of the code.

Conservation of coastal wetlands: response of suspended solids to hydrochemical gradients

Understanding the biophysical and geochemical dynamics of suspended solids in coastal wetlands is key to assess and predict their response to human and natural stressors. However, it is still poorly known in Chile, preventing the design of adequate and timely responses to phenomena lile climate change, droughts, and soil use changes in watersheds, like urbanization.

The objectives of this workl are: (i) to sistematize and creiticallyt review the literature on suspended solids and turbidity in selected coastal wetlands; (ii) to familiarize and apply analytical tools enabling the characterization of the suspended particle dynamics and the related pollutants, either in lab or field models; (iii) to recognize the potential implications of the research findings on the proposal of adaptation/prevention/control.

Financial and economic analysis of urban highways

Based on the information available in the financial statements and operational reports, the aim is to determine the economic profitability of metropolitan urban highways, as well as other economic indicators (e.g.,capital cost per lane-kilometer of road), financial indicators (e.g., cost of debt), and operational indicators (e.g., cost per vehicle-kilometer).
First, the information must be processed and systematized. Second, economic and financial analyses are carried out.

Technical and Social Evaluation of the New Huechuraba Electric Bus Service

This research is being conducted in conjunction with the Engineering for Chile (IPCH) program and the PUENTES UC program.

Since March 2025, the Municipality of Huechuraba has implemented an innovative electric bus system aimed at improving connectivity in areas of the municipality that currently lack formal public transportation, facilitating the mobility of residents to key services such as health centers and municipal services. In this context, Transportation Engineering students are invited to evaluate the design and initial operation of this new community service, which has two electric buses in circulation. Their work will consist of analyzing route efficiency and service frequency, as well as measuring the social impact of the initiative, identifying opportunities for improvement to optimize coverage, accessibility, and the sustainability of the system. At the end of the project, the students must submit a technical diagnosis that justifies the continuity and expansion of the service, along with concrete proposals for its improvement.

The results of this evaluation will be key to supporting applications for future externally funded projects aimed at consolidating and expanding this neighborhood service. From the outset, students will have access to updated maps of the community and technical information on the current route design and bus frequencies, allowing for contextualized work with a real impact on the community's quality of life.

Throughout the semester, we will hold weekly 30-minute meetings, along with progress presentations at a time to be agreed upon by the participants.

Developing an optogenetic printer for the precise control of biological systems

We are developing programmable platforms to precisely control the delivery of instructions to cellular systems. As a model system, we are building a programable “laser printer” capable of delivering spatially and temporally resolved light signals to activate optogenetic programs within cultured cells. This requires creating an interphase that allows dynamic control of the light input, controlling position, intensity and duration of light stimuli.

Bioelctrochemical systems for the treatment of industrial wastewaters

This is an applied research project with industry.
The student will work on laboratory-scale electrofermentation prototypes to stabilize wastewater from different industries, e.g., agriculture, pulp and paper.
The student will learn advanced laboratory techniques to determine the methane potential of organic industrial wastes. Additionally, they will learn how to feed and operate anaerobic and bioelectrochemical reactors, as well as how to monitor and evaluate their performance based on bioenergy production and effluent quality.
If you are interested, please contact me at rolabatut@uc.cl to schedule a meeting to discuss details and answer any questions you may have before making a decision.

Computer Science Museum

This IPRE will involve conducting research on museums and how objects are displayed. Field research will then be conducted to understand the perceptions of relevant stakeholders. Finally, a proposal for the museum will be designed.

Gamification and Mixed Reality in Construction: Review and Research Opportunities

This project focuses on reviewing and analyzing the existing literature on the application of gamification and extended reality technologies (with an emphasis on mixed reality) in the training of construction workers, particularly in the field of ergonomics and the prevention of work-related musculoskeletal disorders.

The study aims to identify:
- The main trends and theoretical approaches in gamification applied to safety and ergonomics education.
- The current state of mixed reality use in construction training environments.
- The limitations and research gaps in integrating these technologies to foster ergonomic behavior change in real workplace contexts.

This study is conceived as an initial step to support future, larger-scale research aimed at developing practical immersive training platforms. At this stage, however, it will be limited to a systematic bibliographic study, with emphasis on recent academic publications.

Electricity Systems Planning and Public Policy

Research on the use and development of planning models for power systems and the design of public policies. In particular, the SWITCH model for generation and transmission expansion will be applied to the Chilean power system. The impact of integrating new technologies into power systems will be quantified, along with other elements such as increasing the use of electricity in the energy matrix and leveraging demand-side flexibility, among others.

Industrial escalation of diagnosis and prognosis methods for infectious diseases

Given the health and economic impacts of respiratory virus infections, our clinical-scientific team has developed rapid, low-cost diagnostic methods to detect RSV, MPV, and an inflammatory cytokine using immunological techniques. This project aims to expand this method by producing large batches of monoclonal antibodies developed by our team, creating a rapid test kit, and validating it through laboratory tests and clinical trials.

Using generative AI for the de novo design of the metamorphic domain of RfaH in its autoinhibited state

The metamorphic protein RfaH is a bacterial virulence factor, which has two domains: NTD and CTD. The CTD reversible interconverts from an alpha-helical into a beta-barrel state through a metamorphic process. Although the possible folding routes between both states have been studied, it is unknown if there are other alternatives of folding topologies for the CTD in the autoinhibited state. In this regard, the use of generative AI tools for de novo protein structure design, such as RFDiffusion, allow to explore novel structures never seen in nature. The purpose of this research is, therefore, to ascertain if RFDiffusion allows to generate novel structures for the CTD of RfaH in the autoinhibited state, as well as analyzing the diversity of generated structures via clustering methods based on structural superposition metrics.

New materials for carbon capture and utilization

The rising concentration of CO₂ in the atmosphere mainly caused by the combustion of fossil fuels is one of the main drivers of global warming. A promising strategy to address this challenge is to capture CO₂ and convert it into valuable products such as methanol, which is widely used as both a clean fuel and an industrial feedstock. However, conventional copper‑based catalysts tend to lose activity quickly, limiting the efficiency of current processes.
This project aims to develop innovative materials capable of capturing and converting CO₂ in a single step, using so‑called dual‑functional materials. The approach focuses on copper‑based perovskites partially substituted with Zn, Ni, or Co. Through a process known as exsolution, these materials generate highly active metallic nanoparticles on their surface. The perovskites will then be combined with β‑zeolite, a porous material that both captures CO₂ and helps stabilize the active catalytic phase.
The work involves the synthesis of these hybrid materials, their characterization using advanced techniques such as X‑ray diffraction, gas adsorption, electron microscopy, and X‑ray photoelectron spectroscopy, and their testing in a fixed‑bed reactor to evaluate their ability to convert CO₂ and hydrogen into methanol. The expectation is that the perovskite-zeolite combination will yield catalysts that are more stable, active, and selective, contributing to cleaner technologies for sustainable fuel production.

Propulsion of Ships Powered by Batteries and Green Hydrogen

The project was awarded under the 2025 Regular Technology Rings Competition of the National Research and Development Agency (ANID). The project aims to develop a comprehensive framework for the efficient management of electric vessels that use batteries and hydrogen as energy sources. The initiative aligns with the Chilean Navy's National Green Hydrogen Strategy and its Continuous National Shipbuilding Plan, aiming to strengthen the sustainability and competitiveness of the national maritime sector. The project also has the support of the Chilean Navy and the companies Saam Towage and Dhemax, which reinforces its applied focus and its potential impact on national industry.

Main lines of research:

1. Optimal management of energy vectors under uncertainty.

2. The second focuses on electrical infrastructure and microgrids.

3. Electric propulsion and conversion systems.

IPRE is focused on line 3 but has potential for collaboration in the other lines.

Experimental Analysis and Modeling of Collective Cancer Cell Migration

This project offers the opportunity to analyze experimental data from a cancer cell migration assay and translate the findings into a computational model, extending an existing Julia-based framework for simulating collective cell migration (see: https://doi.org/10.1039/c5ib00092k; https://doi.org/10.1101/2025.08.28.672905). The student will learn to process and analyze migration data, then implement it within a simulation platform using Julia or Python—modifying and expanding the model, performing parameter sweeps, and exploring how mechanical interactions influence emergent collective behaviors.
We seek motivated and independent students committed to applying computational tools to improve our understanding of cancer progression.
Let me know if you'd like it more specific about the type of migration assay or the analysis steps involved.

Evaluation of Multifrequency Deep Image Prior for Real-Time 0.55 T Radial Cardiac Cine MRI

Cardiac cine Magnetic Resonance Imaging (MRI) is the gold standard for assessing heart function, but conventional techniques rely on electrocardiogram(ECG)-based acquisitions over multiple heartbeats, which limits temporal resolution and excludes patients with irregular heart rhythms. Recent advances in artificial intelligence have introduced Time-Dependent Deep Image Prior (TD-DIP), a powerful method that enables high–temporal-resolution cardiac imaging from very short MRI acquisitions. However, standard TD-DIP still depends on ECG signals, restricting its applicability in patients with arrhythmias. The Multifrequency TD-DIP framework overcomes this limitation by learning cardiac motion directly from the data—without requiring ECG input. This method has shown promising results at 1.5 T using spiral acquisitions. The objective of this project is to implement and evaluate Multifrequency TD-DIP for radial cardiac cine MRI at 0.55 T. Low-field MRI systems offer improved patient comfort, lower costs, and greater accessibility, but they also present exciting challenges due to reduced signal-to-noise ratio (SNR). This project offers hands-on experience at the intersection of MRI physics, signal processing, and deep learning, contributing to more accessible and patient-friendly cardiac MR imaging technologies.

Universal Discontinuity Index–Driven Digital Twins for Multiscale Damage and Stability in Brittle Rock Masses

This IPre project is embedded within a broad research framework focused on the development of Digital Twin–based approaches for rock mass behavior in mining and underground engineering. The research aims to advance the understanding of how geometric discontinuities, stress conditions, and scale effects jointly control damage evolution, anisotropy, and structural stability in brittle rock masses.
A central element of this framework is the Universal Discontinuity Index (UDi), which serves as a unifying structural descriptor to quantify fracture activation, mechanical degradation, and failure mechanisms across a wide range of mining-related problems. By integrating UDi into Digital Twin models, the research establishes a consistent link between rock mass geometry, loading conditions, and mechanical response, enabling systematic interpretation across different engineering contexts.
The Digital Twin framework developed in this project is applicable to multiple domains of mining engineering, including:
• uniaxial and confined rock strength (UCS and biaxial conditions),
• pillar stability and strength evolution,
• support and reinforcement design in jointed rock masses,
• anisotropic fracture behavior associated with oriented discontinuities,
• stability assessment of underground excavations at different scales.
Within this approach, numerical and experimental models are treated as digital representations of physical rock systems, where damage indicators such as fracture intensity, activation mode, kinematic response, and UDi evolve together with stress and deformation. This enables a unified interpretation of failure processes, independent of the specific mining application.

Deep Learning–Based T1 and T2 3D Whole-Heart Mapping for Joint T1/T2 MRI

T1 and T2 mapping are cardiac Magnetic Resonance Imaging (MRI) techniques that have been shown to provide objective information about the myocardium, enabling the assessment of cardiac diseases that cannot be diagnosed using conventional cardiac imaging. Joint T1/T2 sequence enables the acquisition of simultaneous 3D T1 and T2 mapping from 3 water volumes. Since T1 and T2 maps are now estimated in 3D, this process can be time-consuming. The goal of this project is to train a neural network to directly estimate T1 and T2 maps from a novel joint T1/T2 sequence at 0.55T, reducing processing time and improving its accuracy.

Public Policy Monitor

Through the analysis of surveys and modern econometric statistics, students will work on the preparation of reports applied to labor economics, migration, and the control of criminal activity.

Although the grade will be individual, opportunities for pair or group work will be offered. Applied Econometrics (ICS2563) is a fundamental requirement, and priority will be given to those with Advanced Econometrics (ICS3564) or similar coursework in Database Management or Machine Learning. Please indicate your experience in one of these areas in your application.

Implementation of a Sensory Panel Training Methodology for the Evaluation of Plant-Protein-Based Food Products

The growing development of plant-protein-based food products requires specialized sensory methodologies that enable accurate and reproducible evaluation of attributes affecting consumer acceptance. This initiative proposes the implementation and validation of a standardized sensory panel training methodology for plant-based products, addressing key challenges such as off-flavor perception, texture characterization, and hedonic attributes. The opportunity is embedded within a FONDEF initiative focused on novel protein sources for food applications in Chile, contributing to the development of specialized sensory capabilities with strong potential for technological transfer.

PRISMA AI Program: Data for Better Health

This program aims to improve initial access to the healthcare system through artificial intelligence tools that support early clinical guidance and patient decision-making, helping optimize referrals and reduce pressure on emergency services. To achieve this, a set of interoperable solutions will be developed, integrated with clinical systems and trained using local data under robust data governance and security standards.

The portfolio includes projects such as P02 Clinical orientation chatbot (intelligent triage), P03 Ambient Listening for automated consultation capture, P04 Automatic clinical summaries using NLP, P05 Online DRG coding assistant, and P06 Digital clinical prescription, which aim to improve clinical workflow efficiency, strengthen medical record quality, and support clinical decision-making.
All developments are carried out jointly with the implementing partner Red UC CHRISTUS.

Development of an automated system for bioreactor monitoring

In this research, the student will develop a data acquisition system (DAQ) for the measurement and continuous monitoring of pH, temperature, and mainly the biogas produced by biological reactors used for water treatment and bioenergy production. The student is expected to be able to use Arduino, LabVIEW or similar, in addition to programming tools such as Python, R, or LabVIEW to develop the DAQ. Students will have at their disposal all the necessary materials (e.g. sensors, Arduino, LabVIEW, etc.) to achieve this objective.

Economic Assessment of Urban Runoff Impacts

The objective of this research project is to advance current approaches for evaluating the impacts of urban drainage practices. Specifically, it aims to develop a methodology for quantifying the savings and cost reductions associated with the implementation of storage and infiltration measures within drainage systems.

Diffussion Language Models for Music Generation

The goal of this research opportunity is to work within the CreativAI UC group to explore text diffusion models applied to symbolic music generation. In this internship, you will:
- Study diffusion models
- Implement and develop experiments to evaluate text diffusion models such as the recently released DiffusionGemma
- Attend weekly group meetings to stay up-to-date on topics within the Creative AI field https://creativai-uc.github.io/
(initially Tuesdays 12:30pm-1:30pm)

- Requirements:
* Advanced programming skills or equivalent
* Experience programming neural network models with PyTorch, Keras, TensorFlow, JAX, etc.

Rheological Analysis of Protein-Enriched Rice Flours for Extruded Snack Applications

This project aims to evaluate the rheological behavior of flours and starches obtained from different rice varieties enriched with plant proteins, in order to determine their potential as ingredients for the production of extruded snacks.

The experimental work will consist of measuring viscosity and viscoelastic properties using a rotational rheometer. Through these analyses, the study seeks to understand how protein incorporation modifies the behavior of rice starch and how these changes may influence key product attributes, such as expansion and texture of the resulting snacks.

This work is part of the doctoral thesis of Daniela Muñoz. The study is expected to generate rheological data that can be compared with results from third-generation extrusion studies and extrudate characterization, with the aim of determining the suitability of different rice varieties for the production of high-protein snack products.

The work is expected to be carried out during the second semester of 2026.

Corrosion-LAB: Failure prevention in national industry (2026-II)

CONTEXT: The reliability and useful life of industrial equipment depend to a large extent on the performance of the materials that make up their functional surfaces. Phenomena such as corrosion, wear and degradation generate significant economic losses, decrease the operational availability of assets and can lead to failures with relevant consequences for safety and productivity. In strategic sectors for Chile, such as mining, energy and agribusiness, there is a growing need to select suitable materials for the expected useful life and evaluate the causes of failures that occur early.

OFFER: We are looking for undergraduate students interested in articulating their knowledge for applied research carried out by the "Corrosion-LAB" team. The student can join with a focus on one of the current challenges (to be chosen):
(1) Design and construction of an experimental set-up for FAC (flow accelerated corrosion) resistance evaluation, (2) Development of protocols for fast and accurate analysis of metallic materials ("Materials Science"), (3) Development of protocols for evaluation of polymer performance in aggressive environments ("Materials Science").

Dedication: The 10 crs can be concentrated in one semester or distributed in 5 cr over two semesters.

Erosion-LAB: Wear of Materials by Erosive-Abrasive Flow (2026-II)

CONTEXT: Pulp processing equipment in industry often fails early, despite meeting design and construction standards. The research by the "Erosion-LAB" team addresses the need to ensure operational continuity and extend the useful life of systems that handle turbulent and abrasive flows, such as mining slurries.

OFFER: Collaborate in the development of an intelligent monitoring system that combines acoustic images with flow analysis and material characterization. The student can join our team, applying knowledge from various areas to (choose):
(1) Optimize the design and operation of the turbulent flow simulator (<--"Mechanical Design"),
(2) Develop wear models (<-- "Materials Science"),
(3) Analyze turbulent flow in 3D ("<-- Fluid Mechanics"),
(4) Analyze acoustic signals and images (<-- "Electrical circuits"),
(5) Automate the data acquisition system (<-- "Systems Control").

Dedication: The 10 crs can be concentrated in one semester or distributed in 5 cr over two semesters.

Possible extension as a professional internship (Aeonix) or a master's thesis.

Sintesis and evalation of new catalysts for CO2 hydrogenation

The main objective of this research is to prepare and characterize heterogeneous catalysts based on iron (Fe) or cobalt (Co), subsequently evaluating their performance in a continuous-flow reactor system for the CO2 hydrogenation reaction. Additionally, it aims to thoroughly characterize the different materials using various physicochemical techniques to directly correlate their structural, morphological, and surface properties with the observed catalytic activity and selectivity.

Activities design for robotic manipulador

work on enabling the use of robotic arms using ROS and the design of educational activities focused on modeling, control, and algorithm implementation to support robotics courses. Research on collaborative activities between robotic arms, robot-robot and human-robot interactions

Ventana Celeste: design and development of an immersive digital telescope for astronomy outreach

Ventana Celeste is an astronomy outreach project, developed in partnership with the Interactive Museum Mirador (MIM), that turns a physical-digital telescope into an immersive, accessible experience: the user handles a real device —pointing at the sky, changing magnification, focusing— and explores planets, stars and constellations on a screen, with simulation of real phenomena such as light pollution and atmospheric turbulence (seeing).

The experience comes in complementary modalities: an autonomous (non-mediated) station, intuitive and high-rotation; a mediated station, more realistic and guided by a facilitator; and a home version (web application). The system is also designed to scale to other contexts —such as its eventual use in classrooms—, though that is not the primary focus.

This IPre invites students to join an interdisciplinary team to design, build and improve the device and its software, along two complementary tracks:

• Design and fabrication (CAD/CAM and analog prototyping): 3D modeling and printing, interaction mechanisms (mount, eyepieces, zoom/focus knob), ergonomics and iterative physical prototyping.

• Computer science (software development): the application that generates the sky, orientation sensors, image stabilization, user interface and logging and evaluation tools.

Students will gain experience in human-computer interaction, digital fabrication, software development and science communication, in a project with real impact in museums and other public spaces.

As a curricular activity, the IPre involves committed dedication like any course. In addition, the project has funding that allows outstanding contributions —from especially motivated students who take on a prominent role— to be recognized with financial support.

Can winter storms help restore eroding beaches? Remote sensing of beaches and inlets on the Chilean coast.

Remote sensing of the earth allows us to observe and quantify spatial and temporal processes. On the Chilean coast, beach erosion is increasing vulnerability of ecosystems and infrastructure to climate change, but this process is non-linear. Winter storms in 2023 and 2024 brought both freshwater and watershed sediments to the coast. This iPre will test the hypothesis that the 2023 and 2024 winter storms deposited litoral grade sediments on the Chilean coast, allowing for beach renewal.

The project will use remote sensing (e.g. CoastSat which uses Sentinel-2 and Landsat 8/9) to detect shoreline changes focusing on beaches with river mouths (Vos et al. 2019). This work will link to ongoing work at the Ligua-Petorca estuary where a camera at the inlet is also recording inlet and beach changes on a finer resolution.

The objective will be to test the hypothesis by looking at coastal shoreline changes, and relate them to oceanic and watershed processes.

This project requires programming skills (e.g. Coastsat is written in Python). Experience in GIS and time-series analysis is beneficial but not a requirement. This project may also include fieldwork to validate measurements.

References

Sánchez-García, E., Palomar-Vázquez, J. M., Pardo-Pascual, J. E., Almonacid-Caballer, J., Cabezas-Rabadán, C., & Gómez-Pujol, L. (2020). An efficient protocol for accurate and massive shoreline definition from mid-resolution satellite imagery. Coastal Engineering, 160, 103732.

Vos, K., Splinter, K. D., Harley, M. D., Simmons, J. A., & Turner, I. L. (2019). CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery. Environmental Modelling & Software, 122, 104528.

Semi-supervised automatic segmentation in cardiac magnetic resonance imaging

Medical image segmentation is a labor-intensive and time-consuming task, which presents a significant challenge in clinical practice. This is exacerbated by the scarcity of data manually annotated by experts, as the labeling of 3D volumes requires specialized personnel and extensive hours of work. In this context, artificial intelligence, and particularly semi-supervised learning, emerges as a promising solution: it allows for leveraging both a small set of labeled images and a larger volume of unlabeled images, reducing the reliance on manual annotations without sacrificing accuracy.
This work aims to utilize state-of-the-art neural network architectures, adapted for semi-supervised frameworks, to automatically segment various contrasts and 3D cardiac MRI maps, optimizing the annotation process and improving the model's accuracy even with limited labeled data.

Design and Research: Computational Thinking from a Phone

Join a project that brings physical computing to schools that can't afford class sets of kits. The idea: rebuild the hands-on, tangible value of physical computing using the smartphone students already own, plus everyday materials like cardboard, programming with Blockly blocks on the Protobject platform. This lowers the cost barrier and brings real equity to Chilean classrooms.

Your role is to own the quality of a progression of several activities: reviewing, iterating, and redesigning them against clear computational-thinking objectives, refining the texts, the pedagogical progression, and the equivalence check between the phone version and a micro:bit/MakeCode one. This is real iterative design with concrete classroom impact.

You'll gain experience in instructional design, CS education, and mentored research, with the chance to contribute to a paper in progress. We're looking for someone meticulous and creative, interested in CS didactics and physical computing.

As an undergraduate research placement (IPre), it is curricular and calls for committed dedication, like any course. The project also has funding to recognise, with financial support, the exceptional contributions of especially motivated students who take on a standout role.

Mejoramiento de Revisiones de Diseño Basadas en BIM usando Asistentes Virtuales de Inteligencia Artificial (2026-2)

IoP para estudiantes de pregrado en un innovador proyecto de investigación que combina el modelado de información de construcción (BIM), la realidad virtual (VR) y la inteligencia artificial (AI). El objetivo es desarrollar y optimizar asistentes virtuales basados en técnicas de inteligencia artificial para mejorar las revisiones de diseño en la industria de Arquitectura, Ingeniería y Construcción (AEC). Los participantes tendrán la oportunidad de trabajar en áreas emergentes, como la recuperación de información basada en AI (IR), la integración de modelos de lenguaje como GPT, y la mejora de la interacción en entornos de realidad virtual.

El proyecto implica diseñar y desarrollar un asistente virtual que utilice inteligencia artificial para facilitar la recuperación de información desde datos BIM en un entorno VR, mejorando así la comprensión del diseño, la colaboración entre stakeholders y la eficiencia del proceso de revisión de diseño.

Fronteras de la IA Generativa: Arquitecturas de Agentes y Modelos Multimodales para Dominios de Alto Impacto (2026-2)

¿Te imaginas desarrollar sistemas de IA que puedan razonar, crear y colaborar como nunca antes? Este proyecto te invita a sumergirte en las fronteras de la inteligencia artificial generativa, explorando Modelos de Lenguaje Multimodal (LMM) y LLM a través de arquitecturas de agentes inteligentes. Inspirados en laboratorios disruptivos (OpenAI, Google DeepMind, Anthropic), exploraremos cómo revolucionar sectores como educación adaptativa, diagnóstico médico, ingeniería automatizada e industrias creativas. En este proyecto desarrollarás: Arquitecturas de agentes IA que integren LMMs y LLMs para resolver problemas complejos; Sistemas de razonamiento explicable y Prototipos funcionales que demuestren el potencial transformador en aplicaciones reales

¿Por qué este proyecto? No es solo académico: es tu oportunidad de prepararte para el futuro de la IA contribuyendo en dominios de alto impacto. ¿Listo para explorar donde la creatividad humana se encuentra con la IA generativa?

Innovation, AI Technologies, and Sustainability in Companies and Startups 2026-2

- Topic options: Innovation, digital transformation, and the use of artificial intelligence in companies; eco-innovation as a response to sustainability challenges; factors influencing the success of fintechs and technology-based startups; wage gaps and sustainability.
- Methodological options: Econometric analysis, analysis based on natural language processing, database construction, and systematic literature review.
- The specific topic and methodology will be discussed with the applicant during the interview. Each IPre addresses only one of the topic options and, at most, two methodological techniques.
- To apply, please send me a CV and "ficha académica" to gvaldesu@uc.cl by July 14.

Implementation of Sensory Evaluation Methodologies for the Development of Meat Analogues

This project focuses on the development of meat analogues based on texturized plant proteins, with a particular emphasis on the evaluation of their sensory quality. Sensory characterization is a key step in understanding consumer acceptance of these products and in relating their sensory attributes to the physicochemical and structural properties developed during processing. To achieve this, a trained sensory panel must be established and coordinated to ensure reliable and reproducible evaluations.
Project Objective
The undergraduate researcher will support the implementation and coordination of the project's trained sensory panel by participating in the recruitment, selection, and training of panelists for the evaluation of texturized plant proteins. The student will also assist in planning and conducting sensory evaluation sessions, coordinating panel activities, and ensuring adherence to experimental protocols and project timelines for the evaluation of the developed products.

Assessment of Learning-by-Doing Experiences in Timber Construction Education

This opportunity seeks to assess the educational experience associated with learning-by-doing activities for teaching timber construction systems. The student will support the design, implementation, and analysis of surveys applied to undergraduate students participating in hands-on timber construction activities. The work will focus on evaluating students’ perceptions, learning experience, engagement, and perceived development of technical and transversal skills. The results will contribute to the validation of active learning strategies in timber engineering and construction education, as part of a teaching-focused research project.

Concrete Futures: Technology and Modernization in Chile and Brazil (1955–1975)

How did reinforced concrete contribute to the materialization of sociotechnical imaginaries of the future in Chile and Brazil between 1955 and 1975? This Undergraduate Research Fellowship (IPRE) project proposes a historical and documentary study of reinforced concrete as a pivotal technology that shaped the urban, architectural, and cultural modernization of Latin America during the second half of the twentieth century. Although concrete has been extensively studied from technical and structural perspectives, a critical gap remains regarding its cultural dimension and its role in producing futures imagined through scientific progress and industrial development (Forty, 2012; Cohen, 2011). A comparative analysis between Chile and Brazil reveals how a single material was appropriated within distinct national contexts, uncovering diverse trajectories of articulating the future through the circulation of technical expertise and discursive practices. In the post-war era, concrete became the paradigmatic material for modern planning, the expansion of public infrastructure, and a widespread faith in the technical rationalization of territory. Furthermore, both nations represent critical case studies due to the intensity of their industrialization and urban planning, as well as their active participation in transnational networks of technological knowledge (Gorelik, 2005; Liernur, 2001). This comparative framework contributes to a Latin American genealogy of innovation, framed not as a linear technology transfer from global centers, but as situated processes of appropriation, translation, and resignification of development materials, techniques, and forms.This research operates at the intersection of the history of technology, material culture, innovation studies, and new materialisms. Methodologically, the study relies on the qualitative documentary analysis of historical archives and specialized architecture, engineering, and design journals published between 1955 and 1975. This corpus will allow for the reconstruction of innovation discourses, the mapping of technical knowledge networks, and the semantic deconstruction of the future as embedded in concrete. The empirical material will be systematized using conceptual profiles, content analysis, and digital data visualization tools.The project aims to advance the understanding of the genealogy of innovation in Latin America by shifting the scholarly focus from abstract definitions toward concrete material substrates. Additionally, it offers a critical reading of concrete as a technology that not only transformed the built landscape but also materialized the socio-political futures of developmentalist modernization. Furthermore, this research enhances engineering education by fostering a sociotechnical understanding of material innovations as phenomena that are simultaneously technical, aesthetic, political, and socio-environmental. Ultimately, the project contributes to the interdisciplinary reappraisal of twentieth-century concrete heritage.
Research Lines
Line 1: Literatur Rewiew. Development of an academic dossier that compiles, classifies, and critically analyzes specialized literature on concrete across the fields of innovation, material culture, history of technology, modernization, developmentalism, and technological optimism. Deliverables: Analytical index cards reviewing books, scientific papers, theses, journals, and relevant archival collections.Line 2: Digital Analytical Repository and Evidence ArchiveConstruction of a structured database consisting of analytical case profiles that link architectural, design, and artistic works executed in concrete with their primary documentary sources (including project files, historical photographs, blueprints, technical specs, and institutional records).Final Deliverables: Analytical case-study profiles and digital data visualizations mapping technological circulation patterns, timelines, actor-networks, and geographical clusters.Impact on Academic TrainingCultivation of interdisciplinary competencies that enable students to evaluate material innovations as multifaceted phenomena that operate simultaneously across technical, aesthetic, political, and socio-environmental registers.

Computers, Programming, and Human Rights

We are working on a research project focused on analyzing the role of early computing systems as technologies of solidarity and humanitarian support during the 1970s and 1980s. The objective is to study how the use of punched cards, first-generation microcomputers, and relational databases enabled the tracking of victims, the unification of testimonies, and the cross-referencing of legal data for the defense of human rights.There are multiple specific research lines within the project. Among the tasks you could collaborate on are: (i) Identifying and studying historical technical documents, user manuals, and logic diagrams in memory archives; (ii) Implementing ad hoc methods and digital tools to systematize and visualize the computing workflows of the era; (iii) Designing and conducting qualitative interviews with pioneering engineers, mathematicians, and archivists who operated these systems.

Visualization and annotation of medical images for AI training

In this research opportunity, you will develop a system to visualize and annotate DICOM files of X-ray images to facilitate the creation of datasets with visual grounding, thus enabling you to train more interpretable AI models.

You are expected to have full-stack web development experience (having completed web development and database management courses) and to be interested in researching how to use these tags to train multimodal AI models.

Development of new Astronomical Image Processing algorithms

Research the state of the art, looking for new research gaps or needs in the professional or amateur astronomical imaging communities and develop a new algorithm proposal.

Assessing the Potential of the Feammox Process for the Biological Removal of PFAS from Contaminated Waters

This project will evaluate the potential of the Feammox process as a biotechnological strategy for the degradation and removal of per- and polyfluoroalkyl substances (PFAS), a class of highly persistent emerging contaminants. The study will investigate the ability of enriched microbial consortia to transform these compounds under anaerobic conditions coupled with ferric iron reduction.