PhD in Computational genomics for predictive medicine

University of Helsinki; Helsinki; On-site; EUR 29,000 - 32,000; Full time

Benefits offered by this job

Occupational health care

Sports facilities access

Professional development opportunities

Pension benefits

Job summary

The Barrett lab at the University of Helsinki is recruiting a doctoral researcher (PhD student) in computational genomics for predictive medicine. We analyze multiomic data to discover mechanistically meaningful subtypes of complex human diseases and collaborate with ELLIS Institute Finland and FIMM.

The role involves designing and executing a PhD project, coding, data analysis, and collaboration with international partners, with the aim of advancing molecular endotypes and translational

Qualifications

• Master's degree in computational biology, data science, bioinformatics, or related discipline.
• Proficiency in programming for data analysis in Python or R.
• Research experience in computational biology and/or data science.
• Excellent written and spoken English.

Responsibilities

• Design and implement a PhD research project on computational genomics for predictive medicine.
• Carry out the research project: propose hypotheses, write code, discuss results, and interpret findings.
• Collaborate with team members and international partners.
• Share scientific results via publications and presentations at conferences; contribute to open science.

Skills

Python

R

English

Education

Master's degree in computational biology or data science

Tools

PyTorch

TensorFlow

Git

Job description

The Barrett lab at the University of Helsinki is recruiting a doctoral researcher (PhD student) in computational genomics for predictive medicine. We are jointly affiliated with the ELLIS Institute Finland, the Institute for Molecular Medicine Finland (FIMM), and the Faculty of Medicine at the University of Helsinki. We analyze multiomic data to discover, understand, and measure mechanistically meaningful subtypes of complex human diseases.

We believe that characterizing diseases not by their observed clinical phenotype, but by their molecular and biological endotype, will enable better treatment for patients. This long-held ambition in biomedicine is now poised to be realized due to:

• National research biobanks that collectively include millions of individuals with matched biosamples and detailed electronic health records.
• Large and growing multiomic data sets in samples from these biobanks, including genomics, proteomics, metabolomics, and transcriptomics.
• New machine learning and AI methods to build multiomic models that stratify disease risk, progression, and treatment response by molecular endotypes.

Find examples of research areas and possible projects on our website.

Responsibilities

• Design and implement a PhD research project on a topic related to computational genomics for predictive medicine.
• Carry out the research project: propose hypotheses, write code, think about and discuss results, and interpret findings.
• Collaborate closely with other members of the team, other researchers at the ELLIS Institute and University of Helsinki, and international partners.
• Share scientific results via publications and presentations at local and international conferences, and contribute more broadly to open science (e.g. via pre-prints and open source software).
• Contribute to mentoring and training the next generation of scientists.

Qualifications, experience, and skills

These items are most important for this role. We expect candidates to fulfill most of these:

• Motivation to work collaboratively on hard scientific problems with a pragmatic focus on getting things done.
• Master's degree in computational biology, data science, bioinformatics, or a related discipline (exceptional candidates may be considered coming straight from a bachelor's).
• Proficiency in programming for data analysis in either Python or R.
• Research experience in computational biology and/or data science.
• Excellent written and spoken English.

Nice to have experience

Any of the following are nice experience to have, but not essential. Please don't be put off if you don't have these:

• Working in high-performance or cloud compute environments.
• Working on machine learning problems (e.g. with frameworks such as PyTorch or TensorFlow).
• Research with health care and/or genomics data.
• Developing software in a small team environment with code review and version control.
• Using agentic AI tools (e.g. from Anthropic and OpenAI) while still retaining your own thinking process (see here for more about how we use AI).

This is an opportunity to be one of the first members of a newly established laboratory led by Professor Jeffrey Barrett, who has over 20 years' experience leading genomics research teams. You will benefit from hands-on supervision from Professor Barrett as well as active participation in the intellectual environments at both FIMM (genomics and molecular medicine) and the ELLIS Institute (fundamentals of applied AI). Our team has access to biobank data sets which cumulatively include 2 million individuals (FinnGen, UK Biobank, All of Us, Estonian Biobank). We have access to both local supercomputer facilities as well as extensive cloud computing resources. We also routinely generate new 'omics data in samples available from the Finnish biobank network.

The position is for a fixed term, with a maximum duration of four years. A trial period of six months will be applied. The salary is based on the salary system of the Finnish universities. The starting salary is typically around 2600-2850 EUR per month, depending on the appointees' qualifications and experience, and rises gradually as the PhD work progresses.

The University of Helsinki offers comprehensive services to its employees, including occupational health care, support in access to high quality sports facilities, and many opportunities for professional development.

Standard Finnish pension benefits are provided for university employees.

For more information regarding the position or the research goals of the group, please contact Jeff at jeffrey.c.barrett(at)helsinki.fi.

A diverse and equitable study and work culture is important to us. That is why we do our best to promote an inclusive university community. We encourage all qualified applicants from diverse backgrounds to apply for our positions.

JOIN US TO BUILD A BETTER WORLD – TOGETHER!

The Institute for Molecular Medicine Finland (FIMM) is an international research unit focusing on human genomics and personalized medicine at the Helsinki Institute of Life Science (HiLIFE) of the University of Helsinki - a leading Nordic university with a strong commitment to life science research. As part of Academic Medical Center Helsinki in Meilahti campus FIMM collaborates locally with the Faculty of Medicine, Helsinki University Hospital and National Institute for Health and Welfare. FIMM is part of the Nordic EMBL Partnership for Molecular Medicine, composed of the European Molecular Biology Laboratory (EMBL) and the centres for molecular medicine in Norway, Sweden and Denmark, and the EU-LIFE Community. ELLIS (European Laboratory for Learning and Intelligent Systems) is a major European initiative in AI with a mission to strengthen Europe's AI landscape by connecting top researchers, attracting talent, and fostering strategic collaborations. ELLIS unites leading machine learning researchers in Europe and operates as a multi-centric, pan-European AI Lab, currently spanning 47 research sites. ELLIS Institute Finland was launched in 2025 and is the second institute in the ELLIS network, partnering with Finnish universities. We develop machine learning through fundamental research, with a particular focus on the fundamentals of applied AI: making machine learning more widely and effectively applicable, and better at working with people. AI for Research is one part of this focus. Our faculty works across a broad range of areas, including data-efficient probabilistic machine learning, generative modelling, amortized inference, interactive and cooperative machine learning, and transformative multidisciplinary collaboration. The institute will have a small number of strategic focus areas and the first one is AI for Health, spearheaded by a project to build a nationwide foundation model to support better decision-making in healthcare.

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