Doctoral Student in Deep Learning for Biological Systems

About the role

Four-year fully funded PhD position at KTH developing deep learning methods for modelling biological systems, protein structure, single-cell data, dynamical simulations of cells, or related topics. The PhD is registered at KTH’s School of Electrical Engineering and Computer Science. Deadline 31 July 2026.

Responsibilities

• Build and train deep learning models on biological datasets, proteins, cells, genomic, or imaging data.
• Publish in venues such as NeurIPS, ICML, ICLR, Bioinformatics, and Nature Methods.
• Take five doctoral-level courses across machine learning and computational biology.
• Present results at group meetings and international conferences each year.

Requirements

• Master’s degree in computer science, computational biology, applied mathematics, physics, or a related field, completed by the start date.
• Solid background in machine learning, particularly deep learning.
• Programming proficiency in Python; PyTorch or JAX experience is expected.
• Fluent English.

Nice to have

• Prior publications, even at workshop level.
• Background in molecular biology, genetics, or biophysics.
• Experience with HPC clusters or large-scale training pipelines.
• A first-author preprint on a related topic.

How to apply

Search “Deep Learning for Biological Systems” on KTH’s Varbi portal at the apply link. Submit CV, transcripts, research statement, Master’s thesis, and two references through Varbi before 31 July 2026.