The Postdoctoral fellow will focus on studying drug mechanisms for type 2 diabetes with drug high-throughput screens. Those screens are either complimented with deep molecular characterisation, or gene expression is measured pre- and post-treatment. For this, the fellow will develop innovative methods to explore high-throughput drug screens to derive biomarkers of glucose uptake and study the impact on metabolism of a large drug portfolio, which ultimately will pave the way for personalised medicine in type 2 diabetes.
The aim of the project involves:
- Apply and adapt machine learning and biostatistical methods to the genetic landscape of drug high-throughput screens to predict glucose uptake and investigate impacts on metabolism
- Exploring drug repositioning opportunity of diabetes drugs in cancer and deriving biomarkers of sensitivity for those drugs
- Exploring adverse effects of cancer treatments, which impact the metabolism and glucose uptake, which may reveal new mode-of-actions for type 2 diabetes drugs
- Ph.D. in Bioinformatics, Biostatistics, Physics or equivalent with interest in diabetes, cancer biology and early drug development. Alternatively a Ph.D. in Biotechnology, Biology or equivalent with significant experience and interest in Bioinformatics / Biostatistics
- Excellent programming skills in R, Python and C/C++
- Excellent academic record
- Excellent understanding of at least one: diabetes or cancer biology
- Scientific curiosity, commitment to scientific excellence and ability to work independently
- Highly motivated 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 skills are considered advantageous:
- Experience in machine learning or multivariate statistics
- Knowledge of early drug development
- Working in a Linux environment, with experience of shell scripting, cluster or cloud computing
At the Helmholtz Zentrum München, you can contribute together with leading researchers to the investigation of the development, prevention and treatment of environmental diseases such as diabetes, chronic lung diseases and allergies. In order to further promote your professional development, we offer extensive and targeted research training and career programmes. We support the reconciliation between work and private life with flexible working time models, occupational health management, day care facility for children, a childcare subsidy, Elder Care, as well as other counseling and support services.
Remuneration and benefits are in accordance with the collective agreement for the public service (TV EntgO Bund).
The position is (initially) limited to two years.
The activity involves special knowledge and experience specific to own scientific skills.
As a holder of the Total E-Quality Award, we promote equality of opportunity. In order to increase the proportion of women in management positions, we would be pleased to receive corresponding applications. Qualified applicants with physical disabilities will be given preference.
We are looking forward to receiving your comprehensive online application (Cover letter, CV, certificates, contact details of 2 referees) as a single PDF document until January 30th 2019.
Dr. Anna Sacher
Telefon: 089 3187-2926
Helmholtz Zentrum München
Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)
Institute of Computational Biology
Ingolstädter Landstr. 1
85764 Neuherberg near Munich