PhD Student (m/f/d)

The University Hospital Essen offers first class medical services in the Ruhr metropolis. Every year, 225.000 patients are treated in 30 clinics, 27 institutes and specialized centers. The over 8.000 employees offer medical care with state-of-the art diagnostics and therapies, which meet highest international standards. Patient care is connected with basic and translational research at an internationally competitive level.

The Kocakavuk-Lab “Computational Oncology” of the Department of Hematology and Stem Cell Transplantation (Chair: Prof. Dr. C. Reinhardt) is currently seeking a

PhD Student (m/f/d)

(pay grade: 13 TV-L / 65% – temporary employment)

The pay grade classification depends on the personal and collective legal prerequisites. The employment is provided for the duration of a third-party funded until 31.07.2026. An extension might be possible according to available funding and the maximum employment duration as given by laws regarding scientific fixed-term contracts (Wissenschaftszeitvertragsgesetz).

Your project:

Research in the group of Dr. Emre Kocakavuk at the Department of Hematology and Stem Cell Transplantation, West German Cancer Center, University Hospital Essen focuses on cancer genomics and tumor evolution using large scale sequencing datasets. As part of the project, the candidate will investigate the complex interplay between cancer cells and their tumor immune microenvironment using longitudinally collected DNA and RNA sequencing data. This work will be performed in close collaboration with the Institute for Artificial Intelligence in Medicine (IKIM), which provides state-of the art computational infrastructure.

For this project, we are seeking a highly motivated candidate with a strong background in bioinformatics and computational biology who will develop and apply computational tools to decipher ecotypes and cellular state dynamics in the context of cancer treatment. Our group has expertise in the computational analysis of multi-omic datasets, including Glioma Longitudinal Analysis (GLASS) Consortium and Hartwig Medical Foundation (HMF) datasets. The GLASS, HMF and other datasets, including ICGC-PCAWG and AACR-GENIE, will be available for analysis. In this role, the candidate will work closely with bench-laboratory researchers to verify computational results using molecular biology techniques and functional screenings in in vitro/in vivo models.

As a PhD student in our program, the candidate will have the opportunity to receive exceptional training in theoretical and methodological approaches, both related to the specific project and beyond. The candidate will also be encouraged to present research results at national and international conferences, providing him/her with valuable opportunities to share the work and engage with other leading scholars in the field.

Our group:

As a PhD student in our group, you will be joining a dynamic and collaborative community that values respectful discussion and critical scientific thinking. We utilize cutting-edge methods for longitudinal, multi-level, and single-cell sequencing in preclinical models and patient biospecimens, and our close connections with clinical partners allow us to efficiently translate our basic research into real world applications. Our focus is on using computational tools to gain a deeper understanding of resistance mechanisms and translate this knowledge into precision oncology. We are confident that you will thrive in our stimulating and supportive atmosphere as you advance your research and professional development.

More information ca be found here: https://www.twitter.com/ekocakavuk

Your profile:

·      Completed Diploma or Master degree in natural or life sciences in good standing

·      Proficiency in using Linux/UNIX-based operating systems and working with HPC systems using SLURM

·      Experience with R and/or Python for data analysis, visualization, and statistics

·      Familiarity with workflow management tools such as Snakemake and/or Nextflow

·      Strong coding skills, including version control with Git and thorough script documentation

·      Experience in analysing sequencing data, including sequence alignment, quality control, variant calling/filtering, and gene expression analyses

·      Familiarity with sequencing databases such as TCGA/ICGC, UCSC and Ensembl

·      Basic understanding of cell biology, molecular biology and cancer biology

·      Fluent in scientific English

We offer:

·      Support and supervision for academic endeavors as needed

·      Comprehensive training in state-of-the-art technologies, covering both theory and methodology

·      Opportunities for interdisciplinary networking and international collaborations (e.g. as part of the GLASS consortium)

·      Supporting and enriching work environment with close interdisciplinary contact to dry-lab/wet-lab researchers as well as Clinician Scientists

The University Hospital Essen is an equal opportunity employer. Female scientists are particularly encouraged to apply. The participation in secondary employment depends on the „Hochschulnebentätigkeitsverordnung“ of North-Rhine Westphalia. Disabled applicants will be preferentially considered in case of equivalent qualification.

Please send your complete application documents including the cover letter, your curriculum vitae, copies of all university degrees and contact data of 2 -3 references preferably as a single pdf file within 2 weeks after publication of this advertisement with reference to tender number 1378 to [email protected] or in writing to the University Hospital Essen, Personnel Department, Hufelandstraße 55, 45147 Essen.

We use your data exclusively for application purposes in accordance with the applicable data protection regulations. Further information can be found in the privacy statement on our homepage at: www.uk-essen.de .