Position: Postdoc in Machine Learning & Multi-Omics Oncology
Department: Division of Computational Genomics and Systems Genetics and Clinical Cooperation Unit „Multiparametric Methods for the Early Detection of Prostate Cancer“
Code number: 2021-0090
The German Cancer Research Center is the largest biomedical research institution in Germany. With more than 3,000 employees, we operate an extensive scientific program in the field of cancer research.
The laboratories of Dr. Oliver Stegle (Division of Computational Genomics and Systems Genetics) and Dr. Magdalena Görtz (Clincial Cooperation Unit „Multiparametric Methods for the Early Detection of Prostate Cancer“) have joined forces to develop novel multi-omics profiling technologies for early detection and risk stratification of prostate cancer. In order to advance prostate cancer diagnostics and therapy, we seek to combine machine learning technologies with multi-modal profiling, including omics profiling of tumor samples and liquid biopsies, imaging and clinical information.
Are you interested in developing and applying machine-learning approaches at the forefront of genome medicine?
We are looking for an excellent (senior) bioinformatician / computational scientist to lead our efforts in multi-modal profiling of prostate cancer. Core of the role is the development of integrative analysis approaches to derive disease-relevant signatures in patient samples. For these activities, we aim to build on latent variable approaches such as MOFA developed in our laboratory (see below for relevant prior work). You will also be responsible for applying these methods to a large clinical dataset, which combines omics profiling, liquid biopsies, imaging and clinical information (N>1000 patients), with both a retrospective and prospective collection arm. These activities include responsibility for data processing, data management and the integration of the data modalities into harmonized data structures.
You will be jointly affiliated with the laboratory of Dr. Stegle and Dr. Görtz, and collaborate with clinical partners at DKFZ, University Hospital Heidelberg and (inter)national collaborators. The postdoctoral fellow will be responsible for project management, to oversee the data collection and lead the analysis of the integrated datasets. This is a highly collaborative role across two laboratories and in the context of a major study. Consequently, you are expected to interact with other clinical and computational scientists.
Argelaguet, R. et al. Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets. Mol Syst Biol 14, e8124, doi:10.15252/msb.20178124 (2018).
Kilpinen, H. et al. Common genetic variation drives molecular heterogeneity in human iPSCs. Nature 546, 370-375, doi:10.1038/nature22403 (2017).
Gortz, M. et al. The Value of Prostate-specific Antigen Density for Prostate Imaging-Reporting and Data System 3 Lesions on Multiparametric Magnetic Resonance Imaging: A Strategy to Avoid Unnecessary Prostate Biopsies. Eur Urol Focus, doi:10.1016/j.euf.2019.11.012 (2019).
Nientiedt, C. et al. High prevalence of DNA damage repair gene defects and TP53 alterations in men with treatment-naive metastatic prostate cancer -Results from a prospective pilot study using a 37 gene panel. Urol Oncol 38, 637 e617-637 e627, doi:10.1016/j.urolonc.2020.03.001 (2020).
We are seeking a highly motivated computational postdoctoral research fellow join our interdisciplinary team. You are collaborative, ambitious, meticulous, scientifically adventurous, and curiosity-driven. You hold a PhD in computational biology / bioinformatics / mathematics / physics / computer science or a related discipline. Prior experience in big data analytics, machine learning and modelling is expected. Prior experience in bioinformatics and the analysis and management of NGS data is desirable.
You should have demonstrated the ability to work independently and creatively, set clear goals and communicate within an interdisciplinary setting.
- Interesting, versatile workplace
- International, attractive working environment
- Campus with modern state-of-the-art infrastructure
- Salary according to TV-L including social benefits
- Possibility to work part-time
- Flexible working hours
- Comprehensive further training program
- Access to the DKFZ International Postdoc Program
Earliest possible start date: as soon as possible
Duration: The position is limited to 2 years with the possibility of prolongation.
The position can in principle be part-time.
Application deadline: 07.05.2021
Eva Sabine Blum
Phone +49 6221/42-3601
Please note that we do not accept applications submitted via email.