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We are seeking a talented postdoctoral fellow to work at the interface of structure-informed machine learning and

alchemical free energy calculations as part of an exciting new collaboration between Prof. Dr. Andrea Volkamer and

BIH Einstein Visiting Fellow Prof. Dr. John Chodera. This project seeks to develop an integrated framework for

utilizing both state-of-the-art machine learning approaches and free energy calculations to exploit structural data,

assay data, and scalable computing resources to predict the polypharmacology of small molecule kinase inhibitors.

The postdoc will be embedded in the Volkamer group , situated within the exciting research environment of the

Charité in Berlin, and make a few extended visits to the Chodera lab at the Memorial Sloan Kettering Cancer Center

in New York City. The postdoc will be jointly supervised by Andrea Volkamer and John Chodera, with John Chodera

making several extended visits to the Charité per year under the auspices of the BIH Einstein Visiting Fellowship.

Work will focus on the development of absolute and relative alchemical free energy calculations approaches and

their integration with structure-informed machine learning approaches for predicting ligand binding affinities,

kinase polypharmacology, and the susceptibility of inhibitor binding affinities to clinical resistance mutations. The

postdoc will focus on extending our open source GPU-accelerated Python toolkits (such as openmmtools , yank , and

perses ) for protein-ligand absolute and relative alchemical free energy calculations (built on OpenMM ) and the

development of robust modeling and prediction workflows. This is an exciting opportunity to work at the

intersection of physical modeling, machine learning, and drug discovery as a stepping stone to a career in industry

or academia. Position is pending final confirmation of funding.

Starting date: 1 Feb 2019 or shortly thereafter (for up to 3 years)

Salary: TV-L E13, 100%

Desired qualifications :

● Experience with the theory and practice of small molecule alchemical free energy calculations

● Comfortable with the Python programming language

● Exposure to modern open source software development practices (GitHub, unit tests, continuous

integration)

● Good multidisciplinary team working and communication skills

Bonus qualifications:

● Experience with high-performance computing clusters and/or cloud computing

● Experience with OpenMM or machine learning frameworks such as TensorFlow

● Experience with cheminformatics, computer-aided drug discovery and/or kinase inhibition

How to apply: Interested candidates are invited to send a pre-application to Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! with the

subject line “Postdoc application” that includes:

● a cover letter explaining your motivation, background, and qualifications for the position

● a detailed Curriculum Vitae (including a list of publications)

● contact information of two references

Deadline: 21 Dec 2018

see also:

https://www.charite.de/service/stellenangebot/angebot/detailinfo/dm19818b_postdocresearch_scientist/