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Mittwoch, 16. Januar 2019
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Ph.D. candidate (f/m/diverse) in "Computational method development for CRISPR-CAS9 and pharmacogenomics screens" Aufrufe: 68

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Eingetragen am 20.12.2018
Einsatzort Neuherberg

Jobbeschreibung The Ph.D. project will focus on studying cancer vulnerabilities, drug resistances and drug target identification with CRISPR-CAS9 screens, and explore pharmacogenetic dependencies to identify target populations with tailored biomarkers of drug response. For this, the student will develop innovative computational methods, explore high-throughput drug and CRISPR-CAS9 screens, derive biomarkers of sensitivity, and ultimately pave the way for personalised medicine.

Aim of the project involves:
- Apply and adapt machine learning and biostatistical methods to the genetic landscape of cancer cell lines and CRISPR-CAS9 screens to predict putative drug targets and cancer vulnerabilities
- Exploring high-throughput drug screens to develop novel methods for identifying drug sensitivity biomarker
- Exploiting cancer evolutionary events to build truly innovative methods for personalised medicine
Qualifikationen Your Qualifications
- Master’s Degree in Bioinformatics, Biostatistics, Physics, Informatics or equivalent with interest in cancer biology, diabetes and early drug development. Alternatively a Master’s Degree in Biotechnology, Biology or equivalent with significant experience and interest in Bioinformatics / Biostatistics
- Excellent programming skills in either R, Python or C/C++
- Scientific curiosity and ability to work independently
- Excited to work in a young and multi-disciplinary, collaborative environment including academic and industrial partners
- Excellent communication and presentation skills, including experience in communicating across discipline boundaries
- Fluency in spoken and written English

The following qualifications are considered advantageous:
- Working in a Linux environment, with experience of shell scripting, cluster or cloud computing
- Basic understanding of cancer biology or early drug development
- Experience with the analysis of either CRISPR-CAS9, NGS (transcriptomic and genomic) or pharmacogenomics data (cancer cell line high-throughput screens)
- Experience in machine learning or multivariate statistics
Firma Helmholtz Zentrum München
85764 Neuherberg
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