Welcome to the PhD program

Introduction

Welcome to the DDLS Research School, a Swedish national initiative that aims to train scientists with high competence in data-driven life science and to meet the future needs within data-driven life science in R&D, industry, health care and society at large.

We are thrilled to announce a range of open PhD positions offering unique research opportunities in academia and industry.

Explore Exciting PhD Opportunities in Academia and Industry

The SciLifeLab & Wallenberg National Program for Data-Driven Life Science (DDLS) has recently launched a competitive grant call for the PIs to suggest exciting data-driven research projects and training opportunities for PhD students in academia and industry.

PhD Positions

Explore research opportunities in the following PhD projects in academia and industry focusing on the research areas of Cell and Molecular Biology, Evolution and Biodiversity, Precision Medicine and Diagnostics, Epidemiology and Biology of Infection. As a PhD student you are part of the DDLS Research School, that over the years will enrol 260 PhD students and over 200 post-docs. You will be given the opportunity to network with other PhD students, post-docs and PIs all over Sweden. Additionally, you will be trained to be an expert and a future leader within your field. Read more about the research school here, and the DDLS program here.

The PhD positions are located at different universities within Sweden and the PhD student will also belong to the local research school, when applicable.

Available positions

Academic positions

Cell and Molecular biology

PhD in Generative Modeling for Super Resolution of Brain Imaging, KTH Royal Institute of Technology, Deadline: May 13, 2025

PhD student in Data-driven molecular medicine, Uppsala University, Deadline: May 20, 2025

Doctoral (PhD) student position in applied mathematics and computational biology, Karolinska Institutet, Deadline: May 18, 2025

PhD student in Computerized Image Processing with focus on Data-driven Cell and Molecular Biology in Breast Cancer, Uppsala University, Deadline: May 12, 2025

PhD student in Computational Mathematics, Stockholm University, Deadline: May 14, 2025

Quantitative predictions of protein – DNA interactions from high-throughput biophysical binding data, Stockholm University, Application open July 1

Epidemilogy and biology of infection

PhD position in Data-driven epidemiology and biology of infection, Uppsala University, Deadline: May 28, 2025

Doctoral (PhD) student position in probabilistic models of proteins, Karolinska Institutet, Deadline: May 31, 2025

Evolution and biodiversity

Doctoral student in AI-Based Multispecies Coalescent and Species Delimitation, KTH Royal Institute of Technology, Deadline: May 13, 2025

PhD student position in population genomics, Uppsala University, Deadline: May 15, 2025

Doctoral student in bioinformatics and machine learning, Lund University, Deadline: May 26, 2025

PhD student (DDLS ) in Environmental RNA biology, Stockholm University, Deadline May 26,2025

Precision Medicine and Diagnostics

PhD student in Computerized Image Processing with focus on Applications in data-driven precision medicine and diagnostics, Uppsala University, Deadline: May 12, 2025

Doctoral student in immunotechnology focusing on data-driven precision medicine and diagnostics, Lund University, Deadline: May 13, 2025
Doctoral student in Physics (with focus on machine learning and bone microscopy analysis, Soft Matter Lab), University of Gothenburg, Deadline: May 14, 2025

PhD student in Medical Science (precision medicine), Lund University, Deadline May 17, 2025

PhD student to the Research Group in Radiological Image Analysis, Uppsala University, Deadline: May 19, 2025

Data-Driven Life Science (DDLS) PhD student in Precision Medicine & Diagnostics, Karolinska Institutet, Deadline: May 22 2025

PhD Student in Data-Driven Oncology, Uppsala University, Deadline May 25, 2025

Industrial positions

Industrial PhD student in Data-Driven Life Sciences, Chalmers University of Technology in collaboration with AstraZeneca, Deadline: May 13, 2025

Industrial PhD student in Data-Driven Life Sciences, Chalmers University of Technology in collaboration with AstraZeneca, Closed

Approved Academic PhD Projects in Data-driven Life Science 2025

Cell and molecular biology

Proposal title	Main PI	Affiliation	Co-supervisor(s)	Affiliation
Charting cell differentiation in single-cell omics data via transcription-dynamics-informed optimal transport	Joakim Dahlin	KI	Johan Karlsson	KTH
Enabling variant-aware long read mapping for complex SV detection	Kristoffer Sahlin	SU	Adam Ameur	NGI/Uppsala Genome Centre
Merging and mining of image omics for discovery of early breast cancer progression cues	Ida-Maria  Sintorn	UU	Carina Strell Ingela Lanekoff	UU
Personalized Medication Strategies to Enhance Efficacy and Reduce Adverse Effects	Åsa Johansson	UU	Cemal Erdem Stefan Enroth	UmU
Quantitative predictions of protein – DNA interactions from high-throughput biophysical binding data	Emil Marklund	SU	Arne Elofsson	SciLifeLab, SU
Flow Matching for Managing Missingness in MALDI-MSI: Super Resolution and Completion of Single Cells in Brain Tissue Sections	Hossein Azizpour	KTH	Per Andrén Lukas Käll	UU KTH

Evolution and biodiversity

Proposal title	Main PI	Affiliation	Co-PI(s)	Affiliation
The Archaic within Us:  Functional consequences of  archaic sequences in modern human genomes	Maximilian Larena	UU	Mattias Jakobsson Carina Schlebusch	UU
AI-Based Multispecies Coalescent and Species Delimitation	Jens Lagergren	KTH	Christine Bacon	GU
Transcriptome-guided AI deconvolution of taxonomy (Traident)	Marc Friedländer	SU	Bastian Fromm	UiT The Arctic University of Norway
Discovering patterns in the evolution of codon usage	Ingemar André	LU	Sinisa Bjelic	Linnaeus University

Epidemiology and Biology of infection

Proposal title	Main PI	Affiliation	Co-PI(s)	Affiliation
Autoregressive probabilistic models of protein structure	Benjamin Murrell	KI	Gerald McInerney Daniel Sheward	KI
Data-driven approach to uncover the role of small cryptic plasmids in driving antibiotic resistance evolution	Helen Wang	UU	Luisa Hugerth Dan I. Andersson	SciLifeLab UU

Precision Medicine and Diagnostics

Proposal title	Main PI	Affiliation	Co-PI(s)	Affiliation
Foundation models meet graph-based learning to advance spatial biology towards patient-specific cancer immunotherapy	Nataša Sladoje	UU	Patrick Micke	UU
Precision Medicine for Cardiometabolic Disease: Multi-Modal Analytics to leverage Disease Heterogeneity	Paul Franks	LU	Maria Gomez	LU
Deep learning from images and spatial omics data for precision immuno-oncology	Anna M Sandström Gerdtsson	LU	Catharina Hagerling Patrik Edén Victor Olariu Sara Ek Maria-Louise Elkjaer	LU LU LU LU Hamburg University
Causes and consequences of whole-body composition using imaging, genetic, proteomic and metabolomic data	Joel Kullberg	UU	Tove Fall Susanna Larsson Lars Lind Johan Öfverstedt Elin Lundström	UU
Charting Glioblastoma Invasion with Data-Driven Spatial Perturbation Models	Sven Nelander	UU	Rebecka Jörnsten Mats Nilsson	GU/Chalmers SciLifeLab/SU
Imaging the spatial risk of atherosclerosis – Understanding regional stability through data-driven multidimensional analysis	David Marlevi	KI	Ulf Hedin Ljubica Matic	KI
AI-based Analysis of Cleared Human Bone	Giovanni Volpe	GU	Andrei Chagin	Sahlgrenska Academy/GU

Approved Industrial PhD Projects in Data-driven Life Science 2025

Proposal title	Main PI	Affiliation	Industry Co-PI(s)	Company
Preventing Harmful Chemical Impacts: New AI-based strategies for improved human and environmental health	Erik Kristiansson	Chalmers	Jens Henriksson	Semcon Sweden AB
Deep learning modeling of spatial biology data for expression profile based drug repurposing	Erik Sonnhammer	SU	Dimitri Guala	Merck
Generative AI and data-driven design of lipid nanoparticles for targeted delivery	Maggie Holme	Chalmers	Martina Pannuzzo	AstraZeneca
Advanced Functional Embeddings for AI-Based Health Metrics and Explainable AI in Precision Medicine	Mika Gustafsson	LiU	Maria Lerm	PredictMe AB
Deconvoluting the molecular heterogeneity of drug effects and treatment response	Jochen Schwenk	KTH	Åsa Hedman	Pfizer
Data-Driven Metabolite and Site-of-Metabolism Prediction for Accelerated Drug Discovery	Rocío Mercado	Chalmers	Filip Miljković	AstraZeneca
AlphaFold Cytiva	Arne Elofsson	SU	Sarah McComas	Cytiva

Previously approved PhD Projects in Data-driven Life Science

PhD Recruitment Process for PIs

Academia
PIs need to start the recruitment process according to the local regulations at their university. The final selected candidates need to be approved separately for funding by the DDLS program.

Before the recruitment of the PhD candidate, the PI is requested to summarize the process in a web based template and send us (The template is currently being updated. Please check back later). Based on this documentation, the funding to the final selected candidates will be approved by the DDLS program.

The PIs will also need to sign a Terms and Conditions document for their commitment to PhD project as part of the DDLS program. This document will be sent to the PIs once the PhD candidate has been approved by the DDLS program.

Industry
PIs need to start the recruitment process according to the local regulations at their university. The final selected candidates need to be approved separately for funding by the DDLS program.

Before the recruitment of the PhD candidate, the PI is requested to summarize the process in a web based template and send us (The template is currently being updated. Please check back later). Based on this documentation, the funding to the final selected candidates will be approved by the DDLS program.

The terms and conditions regarding the funding of the industrial PhD projects will be replaced with a decision letter, which will be sent to the industrial PIs once the PhD candidate has been approved by the DDLS program.

The academic PIs will also need to sign a Terms and Conditions document for their commitment to PhD project as part of the DDLS program. This document will be sent to the PIs once the PhD candidate has been approved by the DDLS program.