Bayer is a global enterprise with core competencies in the Life Science fields of health care and agriculture. Its products and services are designed to benefit people and improve their quality of life. At Bayer you have the opportunity to be part of a culture where we value the passion of our employees to innovate and give them the power to change.

PostDoc Machine Learning/Deep Learning (m/f/d)

Your tasks and responsibilities

This position is a part within the EU-funded Innovative Medicines Initiative (IMI) project MELLODDY. With MELLODDY, ten leading Europeanbiopharmaceutical 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. In detail you will:

 

  • Be an active member of a highly interdisciplinary, 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 challenges related to prediction of properties of small molecules and proteomic data
  • Generate direct impact on discovery projects to help patients

 

Who you are

  • PhD degree in bioinformatics, computational biology, 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 modelselection concepts is an imperative prerequisite
  • Expertise in handling, processing, integrating and analyzing data sets related to research in the pharmaceutical industry as well as proficiency in writing codes and experience using a Linux high performance environment
  • Excellent programming skills in Python, additional skills in R, or C++ are an advantage
  • Creative thinker (m/f/d) with outstanding problem-solving ability and the willingness to undertake challenging analysis tasks
  • Strong interpersonal skills with the ability to work effectively both independently and in cross-functional teams
  • Willingness to travel between research sites
  • Excellent verbal and written communication skills in German and English


This is a fixed-term position for 2 years.

Your application

Are you looking for a new challenge where you can show your passion for innovation? Are you interested in working as part of a global team to improve people’s lives? Then send us your online application including cover letter, CV and references.

 

 

 

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Country: Germany
Location: Wuppertal-Aprath
Reference Code: 40274
Functional Area:
Entry Level: