Janne Lehtiö

Karolinska Institutet invites applications for a PhD position in Data-Driven Precision Medicine and Diagnostics as part of the prestigious DDLS Program, focusing on chronic lymphocytic leukemia (CLL). This opportunity is ideal for candidates passionate about leveraging advanced computational methods, multi-omics data, and AI-driven analytics to unravel cancer biology and enable more precise, individualized treatments. The position is based in the Department of Molecular Medicine and Surgery, within the Clinical Genetics Research Group led by Professor Richard Rosenquist Brandell, and includes an interdisciplinary team of bioinformaticians, computational scientists, molecular biologists, and clinical scientists. The research group is located at BioClinicum, Karolinska University Hospital, Solna, and is actively involved in national and international collaborative efforts in CLL. The group generates large-scale multi-omics datasets from patients, including genomics, epigenomics, transcriptomics, and proteomics, complemented by detailed clinical information. Additional data will be generated and integrated with published datasets, providing the PhD student access to exceptionally rich resources for data-driven discovery. Computational resources include NAISS supercomputing and local HPC facilities. The DDLS PhD project aims to develop and apply integrative multi-omics and AI-based computational methods to identify novel molecular subtypes of CLL, discover biomarkers associated with disease progression and treatment response, and unravel regulatory and causal mechanisms underlying therapy resistance. The research will integrate high-dimensional omics data with knowledge graphs, clinical information, and external datasets to generate testable biological hypotheses. The student will participate in DDLS Research School activities, national workshops, and specialized courses in AI, statistics, and integrative omics. Eligibility requires a master’s degree in bioinformatics, computational biology, computer science, engineering, statistics, biomedicine, or a related field. Applicants must demonstrate computational/programming skills (e.g., Python, R), experience with omics data analysis, and proficiency in English equivalent to Swedish upper secondary school English B/English 6. Desired merits include experience with machine learning, deep learning, network analysis, multi-omics integration, large-scale data processing, knowledge graphs, version-controlled pipelines (Git, Nextflow, Snakemake, Docker), background in cancer biology or immunology, and the ability to work independently and collaboratively in multidisciplinary teams. The DDLS Program, funded by the Knut and Alice Wallenberg Foundation, aims to recruit and train the next generation of data-driven life scientists and create globally leading computational and data science capabilities in Sweden. The program is expanding in 2026, with more than 260 PhD students and 200 postdocs participating in the Research School. Strategic research areas include cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology, and biology of infection. Karolinska Institutet offers an inspiring research environment with cutting-edge expertise in medical science, modern laboratory and computational facilities, and strong ties to clinical practice. Employees and students benefit from on-site gym, health promotion services, and a vibrant scientific community. The doctoral student will be employed on a doctoral studentship for up to 4 years full-time, with salary and benefits. Applications must be submitted through the Varbi recruitment system, including a personal letter, CV, degree projects, previous publications, documentation of eligibility, and evidence of relevant skills. Applications can be written in English or Swedish. Selection is based on documented subject knowledge, analytical skill, and other relevant experience. All applicants will be informed when the recruitment is completed. Supervision will be provided by Professor Richard Rosenquist Brandell (clinical genetics, molecular hematology, precision diagnostics), Professor Janne Lehtiö (proteogenomics, multiomics integration, bioinformatics), Dr. Leily Rabbani (bioinformatics, NGS pipelines, machine learning, knowledge graphs), and Dr. Daniel Hägerstrand (molecular biology, large-scale data analysis, functional validation). Join Karolinska Institutet and contribute to the development of next-generation strategies for understanding and treating CLL, making a difference in medical research and health for all.

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.

This PhD position at Karolinska Institutet offers an exciting opportunity to contribute to top-quality medical research in the field of bioinformatics and clinical breast cancer proteomics. The successful candidate will join the Cancer Proteomics Mass Spectrometry research group, led by Professor Janne Lehtiö, at the Science for Life Laboratory (SciLifeLab). The Lehtiö group is renowned for its translational research, aiming to improve cancer treatment through multi-omics tumor data analysis. The team works collaboratively across disciplines to study genes and proteins within biological networks, understand how molecular changes in tumors impact the proteome, and discover new disease biomarkers for therapeutic exploitation. SciLifeLab is a national infrastructure and research center for technology-driven life sciences, with Karolinska Institutet as one of its founding universities. The environment is stimulating and diverse, featuring highly motivated colleagues and cutting-edge technology. The position is part of the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), which is funded by the Knut and Alice Wallenberg Foundation. The DDLS program aims to recruit and train the next generation of data-driven life scientists, focusing on cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, and epidemiology and biology of infection. The doctoral project centers on integrative and translational analysis of omics data from clinical breast cancer cohorts, with a special emphasis on triple-negative breast cancer (TNBC). The candidate will apply established data analysis pipelines and develop new computational strategies for quantitative biological data analysis, validating results with public domain data. The role requires a strong interest in proteomics data analysis, excellent communication skills, and a collaborative mindset. Karolinska Institutet is one of the world's leading medical universities, offering a creative and inspiring environment, individual research projects, well-educated supervision, a wide range of elective courses, and opportunities for international exchange. The doctoral student will be employed on a studentship with a contractual 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 of Science or equivalent in bioinformatics, biology, medicine, computer science, mathematical statistics, or a related field. Applicants must have documented education and experience in bioinformatics data analysis, programming skills in Python and/or R, knowledge of statistical methods, and an understanding of cell and molecular biology. Proficiency in English equivalent to English B/English 6 at Swedish upper secondary school is mandatory. Additional merits include experience with high-throughput omics data (such as MS-based proteomics, NGS), systems biology or systems medicine, large-scale data analysis, integration and visualization, ability to interpret omics data in a biological context, knowledge of breast cancer biology, and strong collaborative and interpersonal skills. Applications should be submitted through the Varbi recruitment system. Required documents include a personal letter, CV, degree projects, previous publications, and certificates of eligibility. The application can be written in English or Swedish. The deadline for applications is May 13, 2026. For more information about the DDLS Research School, visit https://www.scilifelab.se/data-driven/ddls-research-school/ . To apply, use the direct link: Application Portal . Join the Lehtiö lab and DDLS research school to make a difference in cancer research and contribute to better health for all.