JOB DESCRIPTION
We are offering a fully funded PhD position in statistical genomics and precision medicine, based at the Institut de Recerca Germans Trias i Pujol (IGTP, Badalona), under the supervision of Dr. Sílvia Bonàs-Guarch (PI), with co-supervision by Dr. Anne L. Madsen, at the Steno Diabetes Center Aarhus (Aarhus University Hospital, Denmark).
The position is funded through the Spanish “Proyectos de Generación de Conocimiento” call (PEICTI 2024-2027), via an FPI predoctoral contract, and is part of a newly funded research project on the molecular mechanisms underlying beta-cell dysfunction in type 2 diabetes (T2D), aimed at improving patient stratification and treatment optimisation using large-scale human genomics and exposome data.
Project
The PhD candidate will develop mechanism-specific polygenic scores for pancreatic islet beta-cell dysfunction, leveraging pleiotropy and regulatory genomics and generative machine-learning approaches, and will integrate them with exposure-based scores to build a joint genetic-exposure liability model for T2D subtyping. The project moves beyond global genetic risk models towards biologically-grounded interpretable predictor models of T2D heterogeneity, with direct applications in patient stratification and precision medicine. The student will work with large-scale resources including UK Biobank, in-house national GCAT cohort, and Danish population cohorts.
Environment
The candidate will join the Medical Genomics and Precision Medicine for T2D research line, led by Dr. Sílvia Bonàs-Guarch, within the Genomes for Life-GCAT Lab, supervised by Dr. Rafa de Cid. This research line focuses on understanding the molecular and environmental determinants that influence the risk and progression of type 2 diabetes. Within the broader GCAT Lab, the student will have direct access to population genomics infrastructure, computational resources and genetics and exposome expertise. Co-supervision and close collaboration with Dr. Anne L. Madsen (Steno Diabetes Center Aarhus) will provide hands-on training in OGTT-based beta-cell phenotyping and clinical epidemiology. The project is further embedded in an international collaborative network including the Dias & Frazer Lab (Centre for Genomic Regulation), Prof. Torben Hansen (Novo Nordisk Foundation Centre for Basic Metabolic Research, CBMR, Denmark) or Assoc. Prof. Chirag Patel (Harvard Medical School), among others, offering opportunities for training, research stays and high-impact publication
Funding conditions
- 4-year fully funded PhD position (FPI programme), Spanish national funding.
- Support for research stays abroad and conference attendance.
MAIN RESPONSIBILITIES
The successful candidate will contribute to a research project aimed at developing molecularly-informed predictive models for type 2 diabetes by integrating large-scale human genomics and exposome data. The main duties will include:
- Develop mechanism-specific polygenic scores for pancreatic beta-cell dysfunction using GWAS datasets, pleiotropy-informed genetic models, regulatory functional genomics and advanced machine-learning approaches.
- Develop and evaluate exposure-based scores and integrate them with polygenic scores to build joint genetic-exposure liability models for patient stratification and precision medicine.
- Analyse and integrate large-scale genomic, phenotypic and exposome datasets from population cohorts, including the UK Biobank, the GCAT cohort and Danish population cohorts.
- Investigate the molecular and genetic heterogeneity underlying beta-cell dysfunction and type 2 diabetes through advanced statistical, computational and integrative genomics approaches.
- Translate genetic discoveries into clinically interpretable risk prediction models with applications in disease prediction, patient stratification and treatment optimisation.
- Prepare scientific manuscripts, present results at national and international conferences.
- Participate in collaborative research activities and international research stays with project partners, including the Steno Diabetes Center Aarhus (Denmark).
QUALIFICATIONS AND EXPERIENCE
- MSc degree (or equivalent) in Bioinformatics, Computational Biology, Statistics, Data Science, Genetics, Biomedical Sciences, Biotechnology, Computer Science, or a related discipline.
- Candidates must fulfil the eligibility requirements for admission to an official PhD programme at a Spanish university.
- Experience with R/Python.
- Interest in human genetics, omics, complex diseases and data-driven biology.
- Strong analytical and problem-solving skills, ability to work independently within distributed team.
WHAT WE OFFER
- Four-year full-time predoctoral contract (FPI) associated with the research project funded under the Spanish “Proyectos de Generación de Conocimiento” programme (PEICTI 2024–2027).
- Full-time position (100% dedication), in accordance with the applicable regulations for FPI predoctoral contracts.
- Date of incorporation: Jan 2027, upon completion of the recruitment process.
- Gross remuneration according to the salary scales established for FPI predoctoral contracts under the Spanish "Proyectos de Generación de Conocimiento" programme.
- The gross annual remuneration for this position will be determined based on the candidate's experience and skills, distributed over 12 payments.
- Flexible payment (childminding vouchers).
- 23 days holiday and 5 days for personal matters.
- Training capsules by the company.
- Be part of an excellent multidisciplinary research centre with the HRS4R badge.
- Location on the Can Ruti Campus, a first-class translational research environment in the Barcelona area, in a very stimulating scientific environment. The IGTP offers a supportive, friendly and collaborative ecosystem to promote professional development and help you achieve your research goals.
FOR MORE INFORMATION
For more information contact Sílvia Bonàs Guarch (PI) at sbonas@igtp.cat
HOW TO APPLY
Interested persons must attach to the application:- Motivation letter explaining their interest in the position.
- Updated CV.
- Contact of 2-3 references.
- Curricular evaluation: analysis of the curriculum vitae to assess aspects related to training, professional career and experience in positions related to the job position under selection.
- Personal interview: once the résumé has been evaluated, the selected candidates will be called for a personal interview to verify and expand on the information detailed in the résumé and to evaluate aspects related to experience and professional skills.