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 the same time, the Group aims to create value through innovation, growth and high earning power. Bayer is committed to the principles of sustainable development and to its social and ethical responsibilities as a corporate citizen.
Post : Chemoinformatics Data Scientist
Job Description
• Drive incorporation of data science in Bayer Crop Science R&D so that it becomes a core scientific discipline and part of scientists’ daily practice
• Enable data- and model informed innovation and decision making in Small Molecules (SMol) phase projects, by developing and delivering timely, high-quality computational solutions
• Drive the aspiration for digital fluency and data savvy across the SMol organization, foster a digital mindset across Indications
• Collaborate with chemists, biologists, and biochemists to develop models and pipelines to analyze complex biological and chemical data
• Contribute to drug-design activities in SMol research by applying state-of-the-art Machine Learning (ML)/Artificial Intelligence (AI) models, and challenging the status quo by formulating and testing hypotheses via in silico models
• Create generative and predictive models to enable better and faster decision making and lead, design and drive global SMol Data Science and IT Systems
• Work closely with data engineers to put the cutting-edge models and tools you design and develop into production and teach bench scientists to use these tools and drive their adoption
• Identify and evaluate emerging technologies and trends in data science
Candidate Profile
• PhD in Computational Chemistry, Chemoinformatics, Molecular Modelling or a related field and several years of industry experience in chemoinformatics & data science
• Proficiency in Python and demonstrated experience with chemoinformatics libraries, (e.g. RDKit) and machine learning algorithms and frameworks (e.g. Scikit-Learn, CatBoost, PyTorch)
• Proven expertise in applying machine learning and artificial intelligence techniques to computational chemistry and drug design (such as QSAR models, scaffold hopping)
• Demonstrated project leadership experience in Smalll Molecules Drug Design
• Highly self-motivated, strives for scientific excellence and able to manage complexity and to work in an agile manner
• Strong analytical and scientific thinking skills and willing to challenge the status-quo and open to learn experimental set-ups
• Highly developed soft skills and potential for leadership
• Fluent in English, written and verbal
Additional Information
Qualification : PhD
Location : Frankfurt City, Germany
Industry Type : Pharma/ Healthcare/ Clinical research
End Date : 25th December, 2023
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