Research Scientist (all genders) - Machine Learning for Small Molecules

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

Research Scientist (all genders) - Machine Learning for Small Molecules 

Join the Machine Learning Research team at Bayer Pharmaceuticals in Berlin, Germany.  Be at the forefront of advancing drug discovery by modeling pharmaceutically relevant properties of small molecules and drive our efforts towards data-informed computational molecular design for pharmaceutical and agrochemical applications.

YOUR TASKS AND RESPONSIBILITIES

• You push the boundaries of state-of-the-art Machine Learning approaches in small molecules research, focusing on uncertainty estimation, navigating chemical spaces, and modeling the properties of small molecules with pharmaceutical applications, including pharmacodynamics and pharmacokinetics
• Designing and implementing Active Learning and Bayesian optimization strategies to improve pharmaceutically relevant properties of small molecules in chemical spaces of interest is part of your role
• You develop methods for uncertainty estimation to assess the applicability domains of in-silico models and deliver actionable insights to project teams
• Reducing cycle numbers in established design-make-test-analyze approaches to molecular design by augmenting design choices with data-informed compound prioritization is part of your responsibilities
• Acting as a bridging partner between our Crop Science and Pharmaceuticals divisions as part of a life science collaboration falls within your scope of work
• You collaborate closely with experimental units to translate data into tangible project impact
• Exploring uncertainty modeling and Active Learning on modalities beyond small molecules to advance treatment options across therapeutic areas is part of your duties
• Driving continuous improvements in methodologies and processes through your own expertise and experience, and by collaborating with Bayer’s scientists across organizational units, is expected in your role

WHO YOU ARE

We are excited about your talent and passion for this position. Attracting the right talent is important to us. We would be happy to work with you to identify and create the career and development opportunities you are looking for. And if you don't meet all the requirements, we still look forward to receiving your application. We are all constantly learning!

• You hold a PhD in (computational) chemistry, computer science, mathematics, physics, or a related field
• You are experienced in developing and applying Machine Learning approaches with a focus on chemistry and pharmaceutical use cases; a background in deep learning is a plus
• It is an advantage if you have experience with uncertainty estimation and Active Learning, including techniques such as Conformal Predictors and Bayesian models like Gaussian Processes, as well as in working with multiomics data is an advantage
• You are driven and curious to learn about experimental processes, novel mathematical approaches, and Life Science R&D at an industrial scale
• With strong analytical thinking and a scientific mindset, you are ready to challenge the status quo
• You demonstrate the ability to collaborate effectively in interdisciplinary teams and possess excellent interpersonal and communication skills
• Fluent English language skills, both written and spoken round off your profile; knowledge of German is an advantage

WHAT WE OFFER

Our benefits package is flexible, appreciative, and tailored to your lifestyle, because: What matters to you, matters to us! 

• We ensure your financial stability through a competitive compensation package, consisting of an attractive base pay and our annual bonus. In addition, managers can recognize special contributions by granting an individual performance award.
• Whether it’s hybrid work models or part-time arrangements: Whenever it is possible, you will have the flexibility to work how, when and where it is best for you.
• Your family is a top priority. We offer loving company daycare centers at multiple locations, support in finding childcare, time off for the care of elderly or dependent family members, summer camps for children, and much more.
• We support your professional growth by providing access to learning and development opportunities, training programs through the Bayer Learning Academy, development dialogues, as well as coaching and mentoring programs.
• We promote health awareness and opportunities for selfcare through various measures, such as free health checks with the company doctor and our health platform #machfit.
• We embrace diversity by providing an inclusive work environment in which you are welcomed, supported, and encouraged to bring your whole self to work.

FURTHER INFORMATION 

This is a fixed-term contract for two years.

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YOUR APPLICATION

This is your opportunity to tackle the world’s biggest challenges with us: Maintaining our health, feeding growing populations and slowing the rate of climate change. You have a voice, ideas and perspectives and we want to hear them. Because our success begins with you. Be part of something big. Be Bayer.

Bayer welcomes applications from all individuals, regardless of race, national origin, gender, age, physical characteristics, social origin, disability, union membership, religion, family status, pregnancy, sexual orientation, gender identity, gender expression or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination.
 

Location:           ​​ ​   Berlin​

​​Division: ​               Pharmaceuticals​

Reference Code:  826909​