PhD student in Computational Oncology

As a PhD student in Computational Oncology, you will investigate how loss of ECHDC2 shapes metabolic rewiring and oxidative-stress adaptation in therapy-resistant cancers by integrating experimental, clinical and public transcriptomic datasets with state-of-the-art machine learning. The aim is to identify biomarkers and candidate targetable vulnerabilities in therapy-resistant cancers.

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 environment

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 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.

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).