PhD student – Computational Cancer Biology

PhD student – Computational Cancer Biology

We are recruiting a PhD candidate looking to pursue a career in computational cancer biology.

Our group (https://science.ccri.at/research/research-areas/integrative-analysis) at St. Anna Children’s Cancer Research Institute (CCRI) strives to understand cellular development in cancer. Our projects center around two core themes:

  • Integrative analysis of tumors using multi-omics technologies (transcriptomics, epigenomics, proteomics) with a focus on mapping developmental dynamics. We work on rare solid tumors and leukemia in close collaboration with our experimental and clinical partners.
  • Using computational modelling to connect complex biomolecular data to interpretable biological mechanisms. To this end, we apply machine learning to large data collections and we implement interfaces that ease access to these methods for experimental scientists.

Relevant publications: Halbritter et al. Cancer Discovery 2019; Farlik, Halbritter, et al. Cell Stem Cell 2016

As a PhD student, you will:

  • Join an exciting, multi-disciplinary environment with lots of support for your personal and professional development from your supervisor, team, and peers.
  • Analyze different types of biomolecular data from childhood cancers, including single-cell RNA-sequencing, and epigenome analysis (ATAC-seq, ChIP-seq, bisulfite sequencing).
  • Write analysis scripts in R or Python. You will survey and try out different software packages, or may invent and implement new algorithms to achieve your goals.
  • Use and customize conventional or deep machine learning models trained on public data collections and apply them to your data.
  • Take a deep interest in molecular, developmental, and cancer biology and become an expert in some of these areas.
  • Monitor the literature and community resources to keep abreast latest developments and to identify information, data, and methods to integrate in your own work.
  • Write papers, visit conferences, review papers, apply for fellowships, and contribute to grants.

Your qualifications:

    • Master’s degree or equivalent (including an extended thesis project) in computer science, bioinformatics, statistics, applied mathematics, molecular biology, or another relevant subject.
    • Essential: Good programming / scripting skills in R and/or Python); Pragmatic statistics proficiency and sound logic. Experience with Unix environments.
    • Desirable: Experience with bioinformatics or machine learning. Foundations of molecular biology.
  • Excellent verbal and written communication skills in English (German not required).
  • An exceptional level of enthusiasm, determination, and creativity.

 

The institution:

St. Anna Children’s Cancer Research Institute (CCRI) strives to improve treatment for children and adolescents with cancer by bringing together translational and clinical research with open-minded exploration of basic disease mechanisms. Integrally connected with St. Anna Children’s Hospital, experimental and theoretical scientists work side-by-side with oncologists to tackle eminent issues in cancer research and therapy. The CCRI trains a generation of courageous researchers thriving on this interdisciplinary exchange and it hosts state-of-the-art experimental facilities to power this mission. By constant exchange and collaboration with outside institutions we go the extra mile for the benefit of the patient. The CCRI is situated in the center of Vienna, a historic nexus of science in Europe. Vienna hosts a vibrant multi-national community and has repeatedly been cited as the most livable city in the world.

http://science.ccri.at

www.kinderkrebsforschung.at

 

Your application:

Applications must include a motivation letter, curriculum vitae, and contact details of three references. Please send your application or enquiries only by e-mail to Dr. Florian Halbritter, hr@ccri.at. All applications received before November 4th, 2019, will be considered. The position shall remain open until a suitable candidate is found. Start date is flexible.

Successful applicants will be offered a competitive salary according to the Austrian Science Fund FWF; https://www.fwf.ac.at/en/research-funding/personnel-costs/.