Postdoctoral Researcher in Computer Science

About the University of Luxembourg

The University of Luxembourg is an international research university recognized for its multilingual and interdisciplinary approach. The Faculty of Science, Technology and Medicine (FSTM) contributes diverse expertise across Mathematics, Physics, Engineering, Computer Science, Life Sciences, and Medicine. Through its dual mission of teaching and research, FSTM aims to generate and disseminate knowledge, training future generations to understand, explain, and advance society and environment.

The successful candidate will join the Department of Computer Science, gaining access to high-performance computing resources suitable for large-scale machine-learning and foundation-model experiments.

Your Role as a Postdoctoral Researcher in Computer Science

We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025 BRIDGES project GenePPS. This project investigates how machine learning can predict gene perturbation effects for drug discovery. You will play a leading role in developing gene perturbation models that combine foundation models (FMs) and graph neural networks (GNNs) to accelerate therapeutic target identification.

GenePPS aims to overcome current perturbation modelling limitations by integrating large-scale single-cell foundation models with structured biological knowledge in genomic graphs. The project will also deliver efficient algorithms for model training under budget and time constraints, facilitating flexible adoption. This is in close collaboration with Helical-AI, an industrial partner specializing in large-scale genomic foundation models and HPC-enabled model deployment, ensuring translational and scalability considerations.

Responsibilities

• Lead the development of hybrid foundation model–graph neural network architectures for gene perturbation prediction, including novel training strategies under experimental constraints (e.g., active learning, data-efficient approaches).
• Conduct large-scale benchmarking and comparative evaluation of gene perturbation models across diverse single-cell datasets.
• Collaborate closely with Helical-AI on scaling, optimization, and integration of models within an HPC-enabled industrial pipeline.
• Publish research results in leading international conferences and journals in machine learning, computational biology, and AI for science.

The Postdoctoral Researcher will work at the interface of machine learning, genomics, and scientific computing, contributing methodological innovation and translational impact. Close collaboration with Helical-AI ensures model integration into a production-grade platform, with results evaluated in a real-world target identification workflow, including outsourced experimental validation.

Your Profile

We are looking for a candidate passionate about advancing scientific knowledge at the intersection of machine learning and genomic perturbation modelling, bringing strong technical skills and interdisciplinary knowledge.

• PhD degree in computer science, machine learning, computational biology, or a closely related field.
• Strong research track record demonstrated by publications in international venues in machine learning, AI for science, graph learning, or related areas.
• Solid expertise in deep learning, with experience in at least one of the following: foundation models, transformer architectures, graph neural networks, representation learning, or large-scale training.
• Strong mathematical and algorithmic background, capable of designing and analysing novel machine-learning methodologies.
• Excellent programming skills in Python and familiarity with modern ML tooling and reproducible research practices.
• Experience training and deploying machine-learning models on GPU-based systems; familiarity with HPC environments is an advantage.
• Interest in interdisciplinary research at the interface of AI and genomics; prior experience with biological data or computational biology is an advantage.
• Strong teamwork skills and willingness to collaborate closely with academic and industrial partners.
• Fluent written and verbal communication skills in English.

What We Offer

• A multilingual and international environment with staff from 90 countries, part of the “University of the Greater Region” (UniGR).
• A modern and dynamic university with high-quality equipment, strong ties to the business world and the Luxembourg labour market.
• A partner for society and industry, cooperating with European institutions, innovative companies, the Financial Centre, and numerous non-academic partners.

How to Apply

Applications should include:

• Curriculum Vitae
• Cover letter detailing your motivation, background, interests, and career goals aligning with the project.
• PhD diploma or a letter/information indicating the expected defense date.
• Transcript of all modules and results from university-level courses taken.
• List of publications.
• Contact information for 2-3 referees.

Early application is highly encouraged. Please apply ONLINE formally through the HR system; Email applications will not be considered. The University of Luxembourg promotes an inclusive culture and encourages applications from individuals of all backgrounds.

General Information:

• Contract Type: Fixed Term Contract 24 Month
• Work Hours: Full Time 40.0 Hours per Week
• Planned start date: 01/09/2026
• Location: Belval Campus
• Internal Title: Postdoctoral researcher
• Job Reference: UOL08042
• Yearly Gross Salary: EUR 85176 (full time)

Key skills/competency

• Machine Learning
• Genomics
• Foundation Models
• Graph Neural Networks
• Drug Discovery
• AI for Science
• High-Performance Computing
• Python
• Deep Learning
• Computational Biology