Doctoral (PhD) student position in computational proteomics and AI for cancer precision medicine Karolinska Institutet in Sweden

This doctoral (PhD) student position at Karolinska Institutet offers an exciting opportunity to contribute to cutting-edge medical research in cancer precision medicine. The research will be conducted within the Cancer Proteomics Mass Spectrometry (MS) group, led by Professor Janne Lehtiö, at the Department of Oncology-Pathology and based at the Science for Life Laboratory (SciLifeLab) in Stockholm. The Lehtiö group is renowned for its translational and multidisciplinary approach, advancing proteome analysis and its application to personalized cancer treatments. The group develops and applies both experimental and computational methods in proteomics and proteogenomics to understand how genomic alterations and the tumor environment shape the molecular phenotype of cancer. Current research focuses on leukemia and solid tumors, including lung and breast cancer, aiming to identify disease mechanisms, therapeutic vulnerabilities, and immune escape pathways to improve individualized cancer treatments and patient outcomes.

The doctoral student will join a sub-group led by Yanbo Pan, working at the interface of cancer biology, computational proteomics, and AI-driven bioinformatics. The project involves analyzing and integrating diverse proteomics data, including bulk, single-cell, proteogenomics, and spatial proteomics across various cancer types. A major focus is reconstructing signaling networks at single-cell resolution, considering proteoform variation, protein localization, and immune interactions. Advanced machine learning and AI methods, including large language models (LLMs), will be used for functional annotation, information retrieval, and integration from biological databases, literature, and omics datasets, as well as AI-assisted hypothesis generation. These approaches aim to interpret complex cancer proteomics data, identify mechanisms of cancer progression and immune evasion, and prioritize candidate therapeutic targets, supporting future combination therapy and immunotherapy strategies in precision medicine.

The PhD student will be part of a multidisciplinary team with expertise in cancer biology, proteomics, bioinformatics, and oncology. The position includes research work, participation in seminars, scientific writing, and presenting results at meetings. Karolinska Institutet offers a creative and inspiring environment, a wide range of elective courses, and opportunities for international exchanges. The doctoral student will be employed on a studentship with a contractual monthly salary for up to four years full-time. Additional benefits include access to a modern gym and medical care reimbursements.

Eligibility requirements include a master's degree (or equivalent) in computer science, bioinformatics, biostatistics, mathematics, systems biology, or related fields. Strong programming skills in Python and/or R, experience with machine learning, deep learning, or AI methods, and familiarity with omics data analysis are required. Experience with deep learning frameworks (e.g., PyTorch, TensorFlow), large language model frameworks (e.g., Hugging Face Transformers, LangChain), prompt engineering, and retrieval-augmented generation (RAG) methods is a plus. Proficiency in English is necessary, and applicants must meet both general and specific eligibility requirements for doctoral education at Karolinska Institutet. Good communication skills and the ability to work in a multidisciplinary team are essential.

Applications should be submitted through the Varbi recruitment system by May 7, 2026. Required documents include a personal letter, CV, degree projects, previous publications, and documentation of eligibility and skills. Applications can be written in English or Swedish. For more information and to apply, visit the application link provided.