The Computational Genomics Research Lab (CGRLab.github.io/), led by Sina Majidian, at Chalmers, University of Gothenburg, and SciLifeLab is offering two postdoc positions at the intersection of machine learning and comparative genomics. We are interested in understanding how genes evolve across species and how mutations and genetic variants alter biological function. We have been building methods that answer fundamental biological questions and have been developing software tools for the scientific community.
Location:
Data Science and AI division, Department of Computer Science and Engineering. University of Gothenburg and Chalmers University of Technology, Gothenburg & SciLifeLab, Sweden.
Research project 1. Only 2% of the human genome sequence codes for proteins, while most of it consists of noncoding sequences, including regulatory factor binding regions, transposable elements, pseudogenes, conserved elements, and regulatory RNAs. These sequences have important roles in gene expression, cellular function, and development. Pangenomes are collections of genome sequences from one or several species, represented as a set of raw sequences, graphs, or sequence alignments. In this project, we will conduct a comparative study of noncoding genomic regions. The candidate should have expertise in algorithm design and high-performance computing, particularly in the theory of efficient string and data structures, sequence indexing, and large-scale data analysis. Experience with the Burrows–Wheeler transform, pattern matching, and sequence alignment methods is a plus. The candidate will focus on developing efficient indexing methods for the analysis of large-scale DNA sequence data.
Research project 2. This interdisciplinary project focuses on studying genetic variation and determining how different variants co-occur on the same paternal or maternal haplotype, a process known as haplotype phasing. We have previously developed methods for haplotype phasing in humans and other species. In this project, we aim to develop machine learning models to advance the characterization of genetic variations.
Research project 3. De novo genes are genes that arise from previously non-coding DNA rather than being inherited from an existing gene during the course of evolution. They are important because they can introduce new functions and contribute to the evolution and adaptation of organisms. We will develop methods to study how de novo genes evolve in eukaryotes.
- A PhD degree
- At least one high-quality first-author publication
- Proficiency in written and spoken English
- Strong programming skills
Interested candidates are invited to apply here www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job&rmjob=15059 by September 29, 2026.