About the lab
LMCB, the Laboratory for Molecular Cancer Biology (https://vib.be/labs/marine-lab) headed by Professor Jean-Christophe Marine, is located on the University Hospital Campus, Leuven, Belgium, and part of the VIB Center for Cancer Biology and KU Leuven department of Oncology.
We are a dynamic research team leveraging cutting-edge technologies to better understand melanoma biology. We have a particular interest in intra-tumor heterogeneity and its link to therapy resistance & metastatic dissemination. The implementation of single-cell technologies and the integration of single-cell multi-omics, including spatial/imaging, datasets are revolutionizing cancer research. We apply these technologies routinely in our lab and have generated large and unique datasets. We are now looking for a post-doctoral researcher to integrate our bio-informatics team and exploit these rich datasets.
You will be involved in the analysis and data management of single-cell (sc)RNAseq and scATACseq data from various ongoing academic and industrial projects, including the VIB Grand Challenge project POINTILLISM(https://vib.be/grand-challenges-program/personalized-immunotherapy-cancer-patients). You will also be developing your own project(s) on the interpretation and analyses of spatial multi-omics (transcriptomics, proteomics, and metabolomics) datasets.
Good communication skills and a collaborative spirit will be required to integrate our research team, which includes technical staff, graduate and Ph.D. students, and postdocs.
We are looking for a computational biologist who is highly motivated, well-organized, and dynamic with a high level of independence and creative thinking:
- Ph.D. with a topic in one of the following areas: statistics, bioinformatics, or computational biology in a field of (cancer) immunology, molecular biology, or similar.
- A broad bioinformatics experience with good working knowledge in genomics and transcriptomics/pathway biology / (cancer) immunology and deep scientific expertise in next-generation sequencing technologies and (statistical) data analysis. Experience in single-cell sequencing and interest in spatial transcriptomics and proteomics data analysis is mandatory.
- Working proficiency in popular programming languages such as R or Python.
- Fluency in the analysis of large datasets and Linux-based high-performance computing environments.
- A proven and successful publication track record in this field.
- High intrinsic motivation and a strong scientific curiosity.
- Ability to be inventive and to present novel ideas in method development, data analysis, and interpretation.
- Team player that can work independently in a multidisciplinary (international) team
- Excellent oral and written English communication skills
- Proactive, flexible, and problem-solving attitude
- Experience in working with deadlines and being involved in multiple projects
- Duration: full-time contract of one year with the possibility for extensions. You are stimulated to apply for a postdoctoral fellowship.
- (Early) access to state-of-the-art technologies.
- A stimulating (international, multidisciplinary) research environment where quality, professionalism, and team spirit are encouraged.
- The ability to work on scientifically exceptional and high-impact, state-of-the-art projects.
- The opportunity to be part of a young and dynamic team and to provide a meaningful contribution to genetic and oncological research.
- The University of Leuven is one of the most innovative universities in Europe. Leuven is located 20 min. from Brussels, in the center of Europe.
The position is available from November 1st, 2021.
How to apply?
Please complete the online application procedure and include
- A presentation letter describing your motivation
- A full CV including contact details, a list of your publication
- Contacts for further references
For more information please contact Joanna Pozniak (firstname.lastname@example.org).
- O. Marin-Bejar et al., Evolutionary predictability of genetic versus nongenetic resistance to anticancer drugs in melanoma. Cancer Cell 39, 1135-1149 e1138 (2021).
- F. Rambow et al., Toward Minimal Residual Disease-Directed Therapy in Melanoma. Cell 174, 843-855 e819 (2018).
- E. Leucci et al., Melanoma addiction to the long non-coding RNA SAMMSON. Nature 531, 518-522 (2016).