PhD student in Computational Oncology

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PhD student in Computational Oncology

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Vakgebied
Onderzoeker
Functie
PHd
Branche
Onbekend
Aanstelling
Niet nader bepaald
Plaatsingsdatum
13 april 2026
Niveau
Overig
Ervaring
Niet nader bepaald
Dienstverband
Niet nader bepaald

Job description

The project is done in collaboration with the Group of Prof. Sven Rottenberg (University of Bern) and involves the computational analysis of large-scale transcriptomic data from experimental models, patient tumours and public datasets to define ECHDC2-linked metabolic rewiring associated with resistance to radiotherapy, chemotherapy and radioligand therapy.

The PhD candidate will develop and apply computational workflows for bulk and single-cell RNA-seq and spatial profiling data, integrate project-generated data with clinically annotated cohorts and public resources, and help derive ECHDC2-associated transcriptional signatures and prioritised candidate vulnerabilities for downstream validation. The PhD candidate is expected to disseminate the findings in publications, poster presentations and talks both within the UMCG as well as at (inter)national meetings.

Working enviroment

A PhD position for 4 years is available and will be performed in the computational oncology group and co-supervised by Prof. Rudolf Fehrmann and Arkajyoti Bhattacharya. The group uses big-data approaches combined with machine learning (ML) to identify molecular, imaging, or clinicopathological patterns relevant to the pathophysiological behavior and treatment response of tumors. The research group is embedded in the Department of Medical Oncology of the University Medical Center Groningen (UMCG) in the Netherlands, where oncological patient care is coordinated with preclinical and fundamental research on the biology and treatment of cancer.

The Department of Medical Oncology participates in the research institute MoHAD (Mechanisms of Health, Aging and Disease), in which molecular biologists, pharmacists and clinicians work closely together creating an optimal and excellent environment where the biological behaviour of cancer cells, molecular imaging of tumours and novel approaches of cancer targeting are studied.

What do we need

The PhD student will be part of an enthusiastic and multidisciplinary research group and should meet the following requirements:

  • MSc degree in bioinformatics, computational biology, data science, systems biology, biomedical sciences, artificial intelligence, or a related field;
  • Experience with transcriptomic or other omics data analysis, statistics, and programming in R and/or Python;
  • Affinity with machine learning and translational cancer research; experience with large public datasets and/or spatial transcriptomics is an advantage;
  • An enthusiastic, self-motivated, ambitious and proactive team player with good communication skills in written and spoken English.

What do we offer

A full-time appointment for a period of four years (36 hours a week) to be concluded with a PhD examination. After one year, the performance of the candidate will be evaluated to decide whether there is sufficient progress to expect a successful completion of the PhD thesis within the coming three years.
Your salary will be € 3.108 gross per month in the first year, and up to a maximum of € 3.939 gross per month in the last fourth year, based on a full-time appointment. Additionally, the UMCG offers an 8% holiday allowance, an 8.3% year-end bonus.The conditions of employment comply with the Collective Labour Agreement for Medical Centres (CAO-UMC).

Link
Medical-oncology
Rudolffehrmann.nl/wordpress
umcgresearch.org/w/r-s-n-fehrman

For questions about the position

Any questions? Do contact us.

How to apply

Please use the the digital application form at the bottom of this page - only these will be processed.
You can apply until 4 May 2026.
Within half an hour after sending the digital application form you will receive an email- confirmation with further information.
 

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PhD student in Computational Oncology

Groningen
Overig
Niet nader bepaald
Niet nader bepaald
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