Summary
The Institut de Recerca Germans Trias i Pujol (IGTP) is offering a fully funded 4-year PhD position in Statistical Genomics and Precision Medicine, focusing on Type 2 Diabetes (T2D). This FPI-funded position, under the supervision of Dr. Sílvia Bonàs-Guarch and co-supervised by Dr. Anne L. Madsen (Steno Diabetes Center Aarhus, Denmark), aims to improve patient stratification and treatment optimization using large-scale human genomics and exposome data. The successful candidate will develop mechanism-specific polygenic scores and integrate them with exposure-based scores to build joint genetic-exposure liability models for T2D subtyping.
Fully Funded PhD Position in Statistical Genomics and Precision Medicine for Type 2 Diabetes (FPI-Funded)
Designation
PhD Position in Statistical Genomics and Precision Medicine in Type 2 Diabetes (FPI-Funded)
Scholarship Details
| Category | Details |
|---|---|
| Funding Type | Fully funded 4-year PhD position (FPI programme), Spanish national funding. |
| Duration | 4 years |
| Start Date | January 2027 (upon completion of recruitment) |
| Remuneration | Gross annual remuneration according to FPI predoctoral contract salary scales, determined by experience and skills, distributed over 12 payments. Includes flexible payment options and benefits. |
| Benefits | Support for research stays abroad and conference attendance, 23 days holiday + 5 personal days, training capsules, supportive multidisciplinary research environment. |
Research Area
- Statistical Genomics
- Precision Medicine
- Type 2 Diabetes (T2D)
- Molecular Mechanisms of Beta-Cell Dysfunction
- Polygenic Scores
- Regulatory Genomics
- Generative Machine Learning
- Clinical Epidemiology
- Population Genomics
- Exposome Data Analysis
Location
Badalona, Spain (Institut de Recerca Germans Trias i Pujol, IGTP) with collaborative opportunities in Aarhus, Denmark (Steno Diabetes Center Aarhus).
Eligibility/Qualification
Required Qualifications:
- MSc degree (or equivalent) in Bioinformatics, Computational Biology, Statistics, Data Science, Genetics, Biomedical Sciences, Biotechnology, Computer Science, or a related discipline.
- Candidates must fulfill the eligibility requirements for admission to an official PhD program 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 a distributed team.
Scholarship Description
This PhD project is part of a newly funded research initiative focused on understanding the molecular mechanisms underlying beta-cell dysfunction in Type 2 Diabetes (T2D). The candidate will develop mechanism-specific polygenic scores for pancreatic islet beta-cell dysfunction, leveraging pleiotropy, regulatory genomics, and generative machine-learning approaches. These scores will be integrated with exposure-based scores to create a joint genetic-exposure liability model for T2D subtyping. The project utilizes large-scale resources such as UK Biobank, the GCAT cohort, and Danish population cohorts. The successful candidate will join the Medical Genomics and Precision Medicine for T2D research line, benefiting from state-of-the-art population genomics infrastructure, computational resources, and expertise in genetics and exposome research. The position offers hands-on training in OGTT-based beta-cell phenotyping and clinical epidemiology through co-supervision and collaboration with Dr. Anne L. Madsen in Denmark, and engagement with an international collaborative network.
Main Responsibilities:
- 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.
- Analyze and integrate large-scale genomic, phenotypic, and exposome datasets from population cohorts (UK Biobank, GCAT, Danish cohorts).
- Investigate molecular and genetic heterogeneity underlying beta-cell dysfunction and T2D through advanced statistical, computational, and integrative genomics approaches.
- Translate genetic discoveries into clinically interpretable risk prediction models for disease prediction, patient stratification, and treatment optimization.
- Prepare scientific manuscripts and present results at national and international conferences.
- Participate in collaborative research activities and international research stays with project partners.
How to Apply
Interested persons must attach the following documents to their application:
- Motivation letter explaining their interest in the position.
- Updated CV.
- Contact details of 2-3 references.
Applications will be evaluated based on a curricular assessment (training, professional career, experience) followed by a personal interview for selected candidates to verify and expand on the provided information and assess professional skills.
Last Date for Apply
31st October 2026
Apply Link
