Computational Biologist, Oncology
Oncology NIBR
Basel, Switzerland
vor 10 Tg.

Job Description

The Oncology Disease Area at the Novartis Institutes for BioMedical Research (NIBR) is looking for an accomplished PhD-level Computational Biologist to help develop cutting-

edge cancer therapies to benefit patients. Oncology Bioinformatics provides computational biology expertise to the department, with a focus on applications of high-

throughput genomic and biomarker data to target identification, drug discovery, and clinical development. The successful candidate will be highly motivated, creative, and an effective collaborator.

Main Activities :

  • Working with drug discovery teams to apply genomic profiling to target discovery, drug mechanism elucidation, and patient stratification efforts.
  • Contributing to translational research efforts by working with teams to digest clinical study findings, and by supporting translational genomics, model characterization, and data mining efforts.
  • Working closely with clinical teams to analyze and interpret biomarker data from clinical trials (e.g. next-generation sequencing, IHC, proteomics, and digital pathology).
  • Developing and implementing tools and algorithms enabling the efficient analysis of biological data such as transcriptomics, genomics, epigenetics, functional screens and drug sensitivity, to enable new targets identification.
  • Developing innovative analytical methods for new technologies.
  • Education :

    PhD in bioinformatics, biostatistics or computer science and a post-doctoral experience.

    Language :

    Fluency in English (oral / written).

    Skills & Experience :

  • Demonstrated expertise in statistics and statistical learning is required, with practical experience applying machine learning a plus.
  • Demonstrated experience with current analysis methods for next-generation sequencing data is required, including specialized applications such as single cell technologies or ChIPseq a plus.
  • Fluency in one or more programming languages with bioinformatics applications (e.g. Python, R).
  • Knowledge of cancer genomics, clinical and translational science is preferred.
  • Excellent communication skills and a track record of successful collaboration with cross-functional teams.
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