Sina Majidian

Chalmers University of Technology invites applications for a fully funded PhD position in Computational Genomics, based in the Computational Genomics Research (CGR) Lab within the Data Science and AI division. This interdisciplinary project aims to advance our understanding of how genetic variation, especially in noncoding regions of the human genome, contributes to complex diseases. The research focuses on developing innovative methods and models, including efficient pangenomic data structures, evolutionary models, and deep learning architectures trained on genomic data. The CGR lab is at the forefront of computational biology and bioinformatics, leveraging machine learning and statistical analysis to study genome variation and evolution. Candidates will have the opportunity to contribute to ongoing research or propose projects based on their strengths. The Department of Computer Science and Engineering, a joint department of Chalmers and the University of Gothenburg, offers a collaborative and diverse environment with strong industry links and internationally visible research. The division of Data Science and AI develops data-driven methods and AI solutions for intelligent decision-making across society, advancing machine learning from foundations to applications. The CGR lab’s research is accessible at https://cgrlab.github.io/research/ . The position is fully funded, with a starting salary of 34,550 SEK per month (from May 25, 2025), and includes all employee benefits. The appointment is for four years, with 20% teaching or departmental duties, potentially extending to five years. Doctoral studies require physical presence in Sweden throughout the study period, and a valid residence permit must be presented by the start date. Chalmers offers a dynamic working environment in Gothenburg, with generous parental leave, subsidized day care, free schools, and healthcare. The university is committed to gender balance, equality, and inclusion, and offers Swedish courses for non-native speakers. Applicants must hold a relevant Master’s degree (or a 4-year Bachelor’s for those educated outside Sweden), demonstrate strong English communication skills, and be highly proficient in programming (C++, Python, Rust, etc.). Experience in genome sequences and omics data, deep learning, or compressed data structures for strings is required. Additional qualifications such as coursework in bioinformatic algorithms, data structures, deep learning, workflow management systems (nextflow, Snakemake), SLURM, bioinformatics tools, mathematical modeling, and hands-on experience with model training and software development are highly valued. To apply, submit your application in English as PDF files (CV, personal letter, motivation, thesis, transcripts) via the application form at this link . Incomplete applications and those sent by email will not be considered. The deadline for applications is May 1, 2026. For questions, contact Assistant Professor Sina Majidian ([email protected]) or Professor Richard Johansson ([email protected]). Chalmers University of Technology is a leading institution in technology and natural sciences, fostering scientific excellence, innovation, and sustainability. Join us in Gothenburg to contribute to cutting-edge research in computational genomics and make a real impact in the field.

Chalmers University of Technology’s Data Science and AI Division is recruiting two PhD students in machine learning and is also advertising two open postdoc positions in Gothenburg, Sweden. The project is hosted in the CGR Lab / Computational Genomics Research Lab and focuses on developing new deep learning and language-model-style architectures for biologically relevant tasks, including methods and predictive models for DNA sequences and human health applications. The research areas highlighted in the post include convolutional neural networks , transformers , and state-space models , with an emphasis on training models on biological sequence data. The lab notes that no background in biology is required, since domain knowledge will be learned along the way. The environment is described as international, collaborative, and English-speaking, with access to strong compute resources, mentoring, and training support. Ideal applicants have a degree in a quantitative field such as computer science , mathematics , or engineering . The post also asks for programming proficiency, coursework in linear algebra, data structures, and algorithms, and prior experience with deep learning models such as CNNs, GNNs, or transformers. For the postdoc roles, the post mentions competitive salary and benefits. To apply, send a CV and a letter of interest by email to the supervisor. Applications are reviewed immediately, so early contact is encouraged. This is a strong fit for candidates interested in machine learning , bioinformatics , computational genomics , and AI for biology and health .