Research & engineering roles across academia and industry
Medical Data
MRI
CT
Computational Pathology
X-Ray
EEG
ECG
EMG
DICOM / NIfTI / PACS
FHIR / EHR
Artificial Intelligence
Pattern Recognition (PR)
Deep Learning (DL)
Computer Vision (CV)
Machine Learning (ML)
Neural Networks (CNN)
Transfer Learning
Reinforcement Learning (RL)
CS & Mathematics
Object-Oriented Programming
Data Structures
Statistics
Calculus
Algebra
Information Theory
Data Mining
Visual Computing
Preprocessing
Segmentation
Registration
Classification
Regression
Image Tracking
Medical Image Reconstruction
Trustworthy AI
Uncertainty Quantification
Conformal Prediction
Explainability (SHAP)
Monte-Carlo Dropout
Test-Time Augmentation
Model Calibration
Robustness
CV
Research Associate & Teaching Assistant
Jan 2023 – Present
ETH Zurich — Biomedical Data Science Lab · Zurich, CH
Developed multimodal AI pipelines combining lumbar-spine MRI, EHR and gait data for treatment-outcome prediction in low back pain.
Built a harmonisation toolbox and deep-learning models for spine-MRI segmentation, including diffusion-based and U-Net baselines.
Developed MRI-based ranking models for continuous degeneration severity scoring and stenosis classification.
Applied machine learning (random forest, SVM, XGBoost) to clinical data with SHAP explainability for patient-level outcome stratification.
Led secure multimodal data integration and deployment to the Swiss BiomedIT federated network.
Teaching assistant for Foundations of Data Science; supervised 3 M.Sc. students and 2 interns.
Sr. Computer Vision Researcher
May 2021 – Dec 2022
BASF Digital Hub — Advanced Imaging Group · Madrid, ES
Led computer-vision projects and consulted R&D groups on scalable ML workflows and production deployment.
Developed YOLO-based models for microscopy cell counting and bacterial-colony quantification in GLP-compliant imaging pipelines.
Deployed hyperspectral and RGB computer-vision models for plant-disease detection and severity estimation, served via the abaQus app.
Designed and implemented a GrabCut-based method for inpainting-percentage estimation for water-area quantification.
R&D Intern — Deep Learning for Biosignals
Jan 2021 – Apr 2021
Bit Brain Technologies · Zaragoza, ES
Built deep-learning models to decode reach-and-grasp motor intention from EEG for brain–computer interface research.
Reviewed and benchmarked state-of-the-art EEG signal-processing methods.
M.Sc. Thesis Intern & Research Working Student
Oct 2018 – Dec 2020
Siemens Healthineers — MR Cardiology AI & Technology Innovation · Erlangen, DE
Developed a heatmap-regression 3D-CNN to track mitral-valve motion on time-resolved CINE cardiac MRI, reaching 1.66 mm landmark accuracy in the scanner workflow.
Fitted Gaussian models to recover temporally smooth valve-motion curves across the cardiac cycle and extracted clinically relevant motion parameters with high accuracy.
Validated model performance on large-scale datasets and built an interactive dashboard for valve-motion analysis, clustering and anomaly detection.
Assisted deployment of the 3D-CNN into the MRI scanner for predictive motion estimation, filed as an invention disclosure.
Co-invented patent US12239477B2 for automated cardiac-motion extraction.
Earlier, in the SHS Technology Innovation IP team — analysed medical-technology patents, monitored the competitor landscape and supported claims protecting internal inventions.
Broadband & Coverage Intern
Jul 2017 – Sep 2017
Ibertel Engineering Services · Bilbao, ES
Ran mobile-network coverage simulations with radio-propagation models to plan base-station deployment for mobile-phone masts.
Produced technical project documentation and supported RF coverage analysis as project technician.
Tech Stack
Tools I use daily in research and development
Languages
Python
Bash
JavaScript
HTML
C++
MATLAB
SQL
Deep Learning & Computer Vision
PyTorch
Keras
MONAI
OpenCV
YOLO
Hugging Face
scikit-learn
MLOps & DevOps
Git
Docker
FastAPI
GitLab CI/CD
GitHub Actions
DVC
Kubernetes
Voluntary Activities
2023–present
Peer reviewer for Machine Learning for Health (ML4H), the MICCAI EMA Workshop, ISMRM, European Spine Journal, the Journal of Magnetic Resonance Imaging (JMRI) and Scientific Data
2024–present
Member of open-science communities — ORMIR (Open & Reproducible Musculoskeletal Imaging Research), MONAI (Medical Open Network for AI) Human–AI Interaction Working Group, and the ETH AI Center
2023–2025
Diversity Team, AVETH — the academic association of scientific staff at ETH Zurich
2021–present
IEEE Student Member
2015–2019
AEGEE (European Students’ Forum) — organised 4 European conferences (45–60 participants, €3,000–5,000 budgets); IT Officer at AEGEE Europe and Secretary of AEGEE-Bilbao
2016
Co-organiser of the “Knights & Robots” summer course for BEST (Board of European Students of Technology)
2015
Erasmus+ project assistant in Chemnitz, Germany