Doctoral researcher in clinical data science & machine learning

About the LCSB

The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character.

The Luxembourg Centre for Systems Biomedicine (LCSB) is an interdisciplinary research centre of the University of Luxembourg.
We conduct fundamental and translational research in the field of Systems Biology and Biomedicine - in the lab, in the clinic and in silico. We focus on neurodegenerative processes and are especially interested in Alzheimer's and Parkinson's disease and their contributing factors. The LCSB recruits talented scientists from various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly interdisciplinary, and together we contribute to science and society.

Successful candidate will join the Clinical and Translational Informatics, led by Dr. Venkata Satagopam, which focuses on bridging translational medicine and bioinformatics through innovative data integration, visualisation, and advanced analytics. Our research integrates bioinformatics, data science, and IT solutions to advance digital health and translational medicine using a "bench-to-bedside" approach. By harmonising and analysing diverse biomedical data, while focusing on the secure data processing and predictive modelling, we aim to drive progress in translational medicine, improving diagnostics and healthcare solutions. For more information, please visit our page.

Your role

We are looking for a highly motivated PhD candidate interested in AI-based methods, including machine learning and language technologies, for the integration and analysis of clinical, advanced data harmonisation, and next generation research infrastructures. You will contribute to research projects enabling secure, interoperable, and scalable AI-driven use of clinical data for complex diseases such as Alzheimer's and Parkinson's.

You will work within a multidisciplinary environment alongside data scientists, software engineers, biomedical researchers, and clinicians. Your research will focus on developing AI- and LLM-enabled methods and tools to structure, harmonise, and analyse clinical data in a FAIR, privacy-preserving, and clinically meaningful manner, with particular attention to unstructured and multimodal data.

Your responsibilities include:

• Developing and applying machine learning, deep learning, and LLM-based methods to multimodal clinical datasets e.g. EHR, imaging, omics, sensor data
• Designing and implementing NLP pipelines for clinical text processing, semantic annotation, and representation learning
• Developing embedding-based representations of clinical variables and documents to support semantic harmonisation and retrieval
• Designing and implementing Retrieval-Augmented Generation pipelines that combine structured clinical data with unstructured text and external knowledge sources
• Designing and implementing data structuring and harmonisation pipelines, including semantic mapping to clinical data models and ontologies e.g. OMOP CDM, SNOMED CT, FHIR
• Contributing to interoperable and FAIR-compliant data infrastructures that enable secure data sharing, reuse, and AI-driven analytics
• Exploring and implementing federated learning and privacy-preserving AI approaches for distributed clinical datasets
• Collaborating closely with data providers, clinicians, and technical teams to ensure high-quality data integration, validation, and analysis workflows
• Supporting documentation, reproducibility, and dissemination of research outputs e.g. scientific publications, presentations, consortium deliverables
• Participating in international research collaborations and contributing to large-scale EU funded research initiatives

Your profile

Core qualifications:

• MD in computer science, computational biology, bioinformatics, data science, or related fields
• Strong interest in clinical and biomedical data, translational research, and health informatics
• Experience with programming skills in Python and with machine learning and NLP frameworks e.g., PyTorch, TensorFlow, Hugging Face, MONAI
• Understanding of data management, data preprocessing, and handling heterogeneous clinical datasets
• Familiarity with SQL and basic database concepts

Desirable:

• Experience with LLMs, NLP, embeddings, semantic search, or generative AI
• Familiarity with RAG architectures, vector databases, or knowledge-enhanced AI systems
• Experience in deep learning, computer vision, or multimodal data integration
• Exposure to federated learning, privacy preserving analytics, or distributed systems
• Knowledge of clinical data models (OMOP CDM, FHIR) or metadata harmonisation
• Experience with ETL tools, workflow engines, or bigdata frameworks (e.g., Spark, NiFi, KNIME)
• Familiarity with containerisation (Docker) and HPC or GPU computing
• Experience with version control (Git) and reproducible research practices
• Prior involvement in collaborative or EU-funded research projects is an asset

Personal Skills:

• Open-minded, critical thinker with strong analytical and problem-solving skills
• Comfortable working across disciplines and communicating with clinical, technical, and scientific stakeholders

Language Requirements:

Applicants must demonstrate at least B2-level proficiency in the language of their thesis. For details and accepted certificates, please visit the Application for admission - Doctoral Candidates.

We offer

• Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Member of the "University of the Greater Region" (UniGR)
• A modern and dynamic university. High-quality equipment. Close ties to the business world and to the Luxembourg labour market. A unique urban site with excellent infrastructure
• A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous non-academic partners such as ministries, local governments, associations, NGOs …

How to apply

Applications should include:

• Curriculum Vitae
• Cover letter presenting your motivation for this doctoral thesis topic, and explaining how your qualifications and aspirations align with its academic focus
• Transcript of all modules and results from university-level courses taken

Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by Email will not be considered.

All qualified individuals are encouraged to apply. In line with our values, the University of Luxembourg promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students.

General information:

• Contract Type: Fixed Term Contract 36 Month
• Work Hours: Full Time 40.0 Hours per Week
• Location: Belval Campus
• Internal Title: Doctoral Researcher
• Job Reference: UOL08033

The yearly gross salary for every PhD at the UL is EUR 41976 (full time).