Postdoctoral Fellow - Computational Biology

Postdoctoral Fellow - Computational Biology

University of Basel

Basel, Switzerland

Your position

The Dixon Lab at University of Basel is seeking a highly motivated research fellow to study neuro-immune interactions in cancer. The role of intra-tumoral neurons is complex and still not fully understood. While some studies suggest they play a critical role in tumor progression and metastasis, others report that they may contribute to anti-tumor immunity. Our lab is dedicated to understanding the innervation landscape of peripheral tumors and its role in immuno-oncology.

We are particularly interested in candidates with experience analyzing cellular and molecular networks underlying tissue homeostasis and disease, especially using single-cell and spatial omics approaches. Our research is highly interdisciplinary, interfacing tumor biology, immunology, and neuroscience, with a strong emphasis on rigorous computational analysis.

Role and Responsibilities

The successful candidate will play a central role in the design, analysis, and interpretation of computational and single-cell biology projects, ensuring high methodological standards, reproducibility, and robust analytical workflows. Responsibilities include:

• Leading computational analyses of single-cell, spatial transcriptomics, and multi-omics datasets;
• Developing and maintaining reproducible, well-documented analysis pipelines;
• Applying and adapting machine learning and AI approaches to biological questions;
• Collaborating closely with experimental scientists to guide study design and data interpretation;
• Contributing to grant writing and shaping the lab's computational strategy;
• Mentoring and advising PhD students and postdoctoral researchers;
• Publishing first-author manuscripts and presenting work at international conferences.

Your profile

• PhD in Computational Biology, Bioinformatics, Computer Science, Mathematics, Biomedical Sciences, or a closely related field;
• Strong background in computational data analysis with a solid understanding of biological and biomedical concepts;
• Expertise in machine learning, AI, or statistical modeling applied to biological data;
• Experience with genomics, transcriptomics, single-cell and/or spatial omics technologies;
• Proficiency in scientific computing frameworks;
• Strong analytical thinking, problem-solving ability, and communication skills;
• Demonstrated ability to work independently while contributing effectively to collaborative projects.

Desirable (but not required): Familiarity with neurobiology, immunology, or cancer biology datasets.