Are you passionate about pushing the boundaries of genomics? We are looking for a Doctoral student to join an exciting project at the intersection of genomics and data science. The successful candidate will develop innovative methods and models to decode the language of the genome and advance our understanding of how genetic variation contributes to complex diseases. The position is based in the Computational Genomics Research (CGR) Lab, within the Data Science and AI division, the Department of Computer Science and Engineering, a joint department of Chalmers and the University of Gothenburg

About the research project 

This highly interdisciplinary project focuses on studying genetic variation in noncoding regions of the human genome by leveraging evolutionary information and developing models that predict the effects of variants. We tackle this challenge via two main directions: (1) developing efficient pangenomic data structures and evolutionary models, and (2) designing deep learning architectures trained on genomic data. The lab is also open to discussing research projects based on the candidate’s strengths.

Who we are looking for

• a Master's degree (*for students with an education earned outside of Sweden, a 4-year Bachelor’s degree is accepted)
• Strong written and verbal communication skills in English
• Highly proficient in a programming language (C++, Python, Rust, …).
• Demonstrated experience in one of the following areas, with a willingness to learn one another: (1) genome sequences and omics data, (2) deep learning, and (3) compressed data structures for strings.


The following experience will strengthen your application:

• Course work in bioinformatic algorithms, data structures and algorithms, and deep learning.

• Experience with workflow management systems (nextflow, Snakemake), SLURM, and bioinformatics tools (aligner, variant caller, samtools, Pysam). Experience in mathematical modeling of DNA or protein evolution.
• Hands-on experience with model training (CNNs, transformers, ...) and libraries (TensorFlow, PyTorch).
• Experience in software and method development.

How to apply:

Apply here.