Arian Lundberg
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Top university
5 days ago
Doctoral student in Multiomics Machine Learning Cancer Bioinformatics KTH Royal Institute of Technology in Sweden
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Sep 12, 2026
Country
Sweden
University
KTH Royal Institute of Technology
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About this position
KTH Royal Institute of Technology is recruiting a doctoral student for a project in multiomics, machine learning, and cancer bioinformatics at KTH/SciLifeLab in Stockholm. The project sits within the third-cycle subject Bio Biotechnology – Cancer Bioinformatics and focuses on precision medicine, cancer progression, and the tumor microenvironment, with an emphasis on genitourinary cancers.
The research will combine bioinformatics-driven analyses, multi-omics data integration, and machine learning methods to investigate factors contributing to tumor progression and their links to cancer progression. The work is especially relevant for candidates interested in cancer biology, computational biology, translational research, and data-intensive biomedical discovery. Collaboration with clinical and translational researchers may be part of the project.
Supervision is proposed by Assist Prof. Arian Lundberg and Prof. Cecilia Williams. The successful candidate will join an active research environment at KTH/SciLifeLab in Stockholm and will work in a setting that values independent research, teamwork, and scientific communication.
Eligibility requires a second-cycle degree or equivalent qualification according to Swedish doctoral admission rules. A master’s degree in bioinformatics, computational biology, or a related field is required, together with a strong background in cancer biology. Practical skills in Bash, R, and/or Python are essential for analysis and multiomics integration. Candidates must also have strong English communication skills and an English level equivalent to English B/6. Two academic or research references are required, including one from a previous supervisor.
Selection will prioritize candidates who can work independently, collaborate effectively, analyze complex issues, show initiative, and manage multiple tasks. Experience with machine learning, multiomics integration, interdisciplinary research, clinical or patient data, HPC, and bioinformatics pipelines is advantageous. The position is a temporary full-time doctoral appointment with salary according to KTH’s doctoral student salary agreement.
Applications must be submitted through KTH’s recruitment system by 2026-09-12. Required documents include diplomas and transcripts, evidence of language qualifications, a CV, an application letter describing research interests and future goals, and representative publications or technical reports.
Funding details
Available
What's required
Applicants must meet Swedish doctoral admission requirements: a second-cycle degree such as a master’s degree, or at least 240 higher education credits including at least 60 second-cycle credits, or equivalent knowledge. A master’s degree in bioinformatics, computational biology, or a related field is required, along with a strong background in cancer biology. Proficiency in Bash, R, and/or Python is essential. Applicants should be able to work independently and in a collaborative team environment, communicate clearly in English, and provide two references from previous academic or research teams, one of which must be the previous supervisor. English proficiency equivalent to English B/6 is mandatory. Preferred qualifications include experience with machine learning, multiomics integration, interdisciplinary research, clinical or cancer patient data, HPC, bioinformatics pipelines or additional programming languages, and strong problem-solving, attention to detail, and scientific literature analysis skills.
How to apply
Apply through KTH’s recruitment system. Submit all required documents: diplomas and transcripts, proof of language requirements, CV, a motivation/application letter, and representative publications or technical reports. Ensure the application is complete and submitted by the deadline.
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