Connectionists: Position / Machine Learning for Drug Discovery

[Djork-Arne Clevert]

We are looking for highly creative and motivated Research Scientist with strong expertise in deep learning and computational life science to enrich our machine learning research group in Berlin, Germany. The position will be advertised within the EU-funded Innovative Medicines Initiative (IMI) project MELLODDY. With MELLODDY, ten leading European biopharmaceutical companies have come together to exchange their research data in a privacy preserving matter to improve the predictive performance of their machine learning models by federated learning. The position will involve research in direct collaboration with scientists from toxicology, medicinal chemistry, high-throughput image analysis, computer scientists, as well as leading European research groups in both academia and industry.
The successful applicant will be part of a cross-organizational team, applying deep learning within the R&D organization on our existing big data sets. She / he will contribute to the implementation of a deep learning platform providing impact on drug discovery and will be responsible for developing, testing and continually improving deep learning methods to predict properties of novel molecules (e.g. drug toxicity, assay bioactivity).

YOUR TASKS AND RESPONSIBILITIES

  *   Active member of a highly interdisciplinary and cross-organizational and cross-corporate team, including scientists from multiple European Pharma companies
  *   Contribute to the implementation and evaluation of a deep learning platform to leverage data in computational chemistry, pharmacokinetics, and toxicology
  *   Extensively validate and further improve the deep learning platform for various property predictions of drug development compounds
  *   Research, design, and implement deep learning algorithms for analysis problems related to prediction of properties of small molecules and proteomic data
  *   Generate direct impact on our discovery projects to help patients
  *   The position is within the Machine Learning Research department, located in Berlin
  *   The applicants are expected to start July 2019
  *   The fix-term position is limited for 36 months

WHO YOU ARE

  *   PhD degree in bioinformatics, computational biology or chemistry, computer science or related fields and a solid background in chemistry, biology and machine learning
  *   Profound experience with state-of-the-art machine learning methods (e.g. graph convolution, representation learning, multitask learning) and model selection concepts is an imperative prerequisite
  *   Excellent programming skills in Python (PyTorch or TensorFlow, RDKit) are essential, additional skills in R, or C++ would be of advantage. Proficiency in writing clean, fast, idiomatic Python code.
  *   Expertise in handling, processing, integrating and analyzing data sets related to research in the pharmaceutical industry
  *   You are a highly creative person with outstanding problem-solving ability and the willingness to undertake challenging analysis tasks
  *   Strong interpersonal skills, excellent written and verbal communication, and the ability to work effectively both independently and in cross-functional teams
  *   Willingness to travel between research sites
  *   Oral and written proficiency in English is mandatory

Dr. Djork-Arné Clevert
Head of Machine Learning Research, Director

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Bayer AG
Research & Development, Pharmaceuticals
Machine Learning Research
Müllerstr. 178, Building S190/328
13353 Berlin, Germany

Phone:    +49 30 468 196745
E-mail:    djork-arne.clevert at bayer.com<mailto:djork-arne.clevert at bayer.com>
Web:       http://www.bayer.com

/// Vorstand: Werner Baumann, Vorsitzender | Liam Condon, Hartmut Klusik, Kemal Malik, Wolfgang Nickl, Stefan Oelrich, Heiko Schipper
/// Vorsitzender des Aufsichtsrats: Werner Wenning
/// Sitz der Gesellschaft: Leverkusen | Amtsgericht Köln, HRB 48248

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