Andreas Barth

Stockholm University is offering a PhD student position in Bioinformatics, with a focus on machine learning applications for complex biological processes. The research will be conducted within the project "Machine Learning for Bioinformatics Applications" at the Department of Biochemistry and Biophysics, in collaboration with SciLifeLab, a leading national center for molecular biosciences. The successful candidate will join the Computational Microscopy for Cell Biology (CMCB) lab, led by Dr. Juliette Griffié, which specializes in advanced data and image analysis, modeling strategies, and interdisciplinary research at the interface of biology, computer science, and mathematics. The project aims to tailor interpretable machine learning and generative AI strategies to study genomic processes using cutting-edge microscopy and DNA sequencing data. Research topics include reinforcement learning for drug design, interpretable ML pipelines for cancer research and diagnostics, and graph neural networks for microscopy data analysis. The lab environment is highly international and multidisciplinary, providing opportunities for collaboration and professional growth. Applicants must have a master's degree or equivalent in engineering, computer science, physics, mathematics, or related fields, or have completed at least 240 ECTS credits (with at least 60 at the advanced level). A strong foundation in life sciences and analytical thinking is required. Eligibility includes at least 90 ECTS credits in chemistry, molecular biology, biotechnology, computer science, mathematics, or physics, and an independent project of at least 30 ECTS credits, plus advanced coursework totaling 60 ECTS credits in relevant fields. Experience with machine learning implementation is required; experience with interpretable ML and/or generative AI is an advantage. Proficiency in English and/or Swedish, analytical ability, creativity, initiative, independence, and teamwork skills are also required. Selection is based on academic performance, relevance of previous studies, references, and interviews. The position is a full-time, fixed-term doctoral employment for up to four years, with a salary according to Stockholm University regulations. The position is fully funded, including salary and social benefits. No tuition fees are required for doctoral students in Sweden. The application deadline is 22 February 2026. For more information, contact Dr. Juliette Griffié ([email protected]) or Professor Andreas Barth ([email protected]). To apply, submit your application via the Stockholm University recruitment system, including a cover letter, CV, and all required documents as specified in the application form. Ensure your application is complete and submitted before the deadline. Refer to the official job posting for detailed instructions.

Stockholm University is inviting applications for a PhD student position in Bioinformatics, with research focused on data-driven life sciences and gene regulatory network inference using multi-omics data. The project, based at the Department of Biochemistry and Biophysics and affiliated with SciLifeLab, aims to develop novel AI and deep learning techniques to enhance gene regulatory network analysis, leveraging gene perturbation designs for single-cell and spatial omics data. The research will contribute to understanding cell type and tissue heterogeneity, with applications in areas such as cancer development. Applicants should have a strong background in bioinformatics, computational biology, or a related field, with specific coursework in Chemistry, Molecular Biology, Biotechnology, Computer Science, Mathematics, or Physics. Essential skills include proficiency in Python, Matlab, R, UNIX, and experience with omics data analysis. Familiarity with deep learning frameworks such as PyTorch or TensorFlow is highly desirable. Candidates must demonstrate strong analytical thinking, creativity, collaboration, and independence, as well as proficiency in written and spoken English. The position is a fixed-term, full-time doctoral employment for up to four years, with a fixed salary. The role may include up to 20% work in teaching, research, or administration. The application deadline is 22 February 2026. Interested candidates should apply via the Stockholm University recruitment portal, submitting a personal letter, CV, and all required documents as specified in the application instructions. For more information, contact Professor Erik Sonnhammer or Professor Andreas Barth. Stockholm University is committed to equal opportunities and a discrimination-free workplace. The research environment is highly collaborative, with access to advanced technical resources and expertise through SciLifeLab, a national center for molecular biosciences.

The Department of Biochemistry and Biophysics at Stockholm University, in collaboration with SciLifeLab—a national center for molecular biosciences—offers a PhD position focused on advancing gene regulatory network (GRN) inference from multi-omics data. SciLifeLab is a leading research center hosted by several Swedish universities, including Stockholm University, and is renowned for its expertise in health and environmental research. The project, titled "Perturbation-based Multi-omics Inference of Gene Regulatory Networks," aims to develop novel AI and deep learning techniques that leverage gene perturbation knowledge to improve GRN inference. Previous research has shown that experimental perturbation designs significantly enhance GRN quality in bulk data. This project will extend these principles to single-cell and spatial multi-omics data, adding cell type and tissue heterogeneity dimensions to causal regulatory analysis. The research will involve creating specialized deep learning architectures to connect data with specific gene perturbations and developing systems to infer perturbation designs from gene expression and chromatin accessibility data. The framework will also be adapted for spatial data to link GRN models to tissue phenotypes, contributing to a better understanding of cancer development and other complex biological processes. Applicants must meet both general and specific entry requirements for postgraduate education. General requirements include completion of a second-cycle degree or equivalent (at least 240 higher education credits, with 60 credits in the second cycle). Specific requirements for the Biochemistry/Bioinformatics program include at least 90 credits in Chemistry, Molecular Biology, Biotechnology, Computer Science, Mathematics, or Physics, and 60 credits at the second cycle level in Life Science, Computer Science, Mathematics, Physics, or Bioinformatics, including a 30-credit thesis. Essential skills are extensive experience with Python, Matlab, and R, good UNIX knowledge, and familiarity with biological omics data analysis. Experience with PyTorch or TensorFlow is highly meriting. Written and oral proficiency in English is required. Selection is based on academic performance, relevant experience, references, interviews, and motivation. The position offers fixed-term employment as a doctoral student for up to four years, with salary and benefits according to Swedish Higher Education Ordinance. Employment may include up to 20% work in education, research, or administration. Stockholm University is committed to equal opportunities and a discrimination-free workplace. For further information, contact Professor Erik Sonnhammer ([email protected]) or Professor and Director of Doctoral Studies Andreas Barth ([email protected]). Applications should be submitted via Stockholm University’s recruitment system, with all required documents attached. Applicants are responsible for ensuring their application is complete and submitted before the deadline. For detailed instructions, refer to the job advertisement and university guidelines. This opportunity is ideal for candidates with strong backgrounds in bioinformatics, computational biology, and AI, seeking to contribute to cutting-edge research in gene regulatory networks and multi-omics analysis at a leading European institution.

PhD student in Bioinformatics at Stockholm University , Department of Biochemistry and Biophysics, within the Computational Microscopy for Cell Biology (CMCB) laboratory led by Assistant Professor Juliette Griffié . The project, titled AI for Multimodal Biology and Microscopy , focuses on developing next-generation generative AI and representation learning methods for integrating and interpreting complex biological datasets, with a strong emphasis on microscopy . The work sits at the intersection of artificial intelligence , computational biology , bioinformatics , and computer vision , and aims to uncover biological mechanisms from large-scale multimodal and heterogeneous data. Applicants should have a strong quantitative background and an MSc in computer science, physics, mathematics, engineering, bioinformatics, or a related field. The ad highlights experience in machine learning and deep learning , ideally in computer vision, plus scientific programming experience (for example a GitHub repository or published/submitted papers). Experience with generative AI or interpretable machine learning is highly desirable, and a genuine interest in biology and interdisciplinary research is essential. The position is hosted at the Department of Biochemistry and Biophysics at Stockholm University and connected to SciLifeLab , a national center for molecular biosciences. The lab’s current directions include interpretable AI pipelines for cancer and autoimmunity, as well as generative and graph neural network approaches for biological imaging. This is a fixed-term salaried doctoral employment for up to four years full-time. The employment may include limited teaching, research, and administration duties. The post is based in Stockholm, Sweden . Application deadline: 2026-11-03. Apply via Stockholm University’s recruitment system and upload a personal letter, CV, and the requested attachments.