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About the Role
We are seeking a Principal Machine Learning Scientist to lead the development, evaluation, and application of machine learning algorithms and workflows for biomolecule characterization and design, accelerating drug discovery. You will identify opportunities to leverage AI capabilities and communicate technological advancements to a diverse range of stakeholders.
Responsibilities
- Lead the development, evaluation, and application of machine learning algorithms and workflows for the characterization and design of biomolecules to accelerate drug discovery.
- Identify opportunities for accelerating ongoing drug discovery projects with internal and external AI capabilities.
- Communicate, educate, and engage with a broad set of stakeholders on the state of technology and the progress of key internal initiatives.
- Keep up to date with the latest advances in computational modeling of biomolecular structure, physics, interactions, and function.
Requirements
- Hold a PhD degree in computational chemistry/biology, chem/bioinformatics, chemical/biological/molecular engineering, or a related field at the intersection of life sciences and computer sciences.
- Have multiple years of relevant post-PhD experience, including professional experience in industry.
- Expertise with state-of-the-art machine learning methods to model biomolecules, for example sequence-to-function models, protein language models, co-folding, inverse folding or steerable generative methods.
- Experience with ML-based workflows towards characterization of biomolecular interactions, assessment of druggability, candidate screening, or design and optimization of therapeutics and delivery systems.
- Experienced in handling, processing, integrating and analyzing large datasets related to drug development research, including sequence, omics, biochemical, biophysical, and structural biology data.
- Expertise in modern bioinformatics tools (e.g., mmseqs, foldseek).
- Strong Python programming skills including the scientific stack (e.g. pytorch, pandas, scikit-learn).
- Experience in collaborative software engineering according to good practices.
- Strong commitment to scientific rigor, a proven track record of scientific achievement, excellent analytical thinking skills, and a high level of self-motivation.
- Excellent written and verbal communication skill in English.
Skills
- Machine learning algorithms
- Biomolecule characterization
- Drug discovery
- AI capabilities
- Computational modeling
- Biomolecular structure
- Biomolecular physics
- Biomolecular interactions
- Biomolecular function
- Sequence-to-function models
- Protein language models
- Co-folding
- Inverse folding
- Steerable generative methods
- ML-based workflows
- Druggability assessment
- Candidate screening
- Therapeutic design
- Therapeutic optimization
- Delivery system design
- Delivery system optimization
- Data handling
- Data processing
- Data integration
- Data analysis
- Drug development research data
- Sequence data
- Omics data
- Biochemical data
- Biophysical data
- Structural biology data
- Bioinformatics tools
- Python programming
- Pytorch
- Pandas
- Scikit-learn
- Collaborative software engineering
- Scientific rigor
- Analytical thinking
- Self-motivation
- Written communication
- Verbal communication
Location
- Berlin
Work Type
- Hybrid work models
- Part-time arrangements
Experience Level
- Multiple years of relevant post-PhD experience
- Professional experience in industry
Education Level
- PhD degree in computational chemistry/biology, chem/bioinformatics, chemical/biological/molecular engineering, or a related field at the intersection of life sciences and computer sciences
Salary/Compensations
- 104.300€ and 126.500€ per year (full-time) plus a variable component
Benefits
- Flexible benefits package
- Competitive salary
- Variable compensation component
- Hybrid work models
- Part-time arrangements
- Company daycare centers
- Support in finding childcare
- Time off for care of elderly or dependent family members
- Summer camps for children
- Access to learning and development opportunities
- Training programs through the Bayer Learning Academy
- Development dialogues
- Coaching programs
- Mentoring programs
- Health awareness promotion
- Selfcare opportunities
- Free health checks with the company doctor
- Inclusive work environment
About the Company
- At Bayer, we are visionaries driven to solve the world's toughest challenges, striving for a world where 'Health for all, Hunger for none' is a reality.
- We foster a culture of energy, curiosity, and dedication, learning from diverse perspectives to expand our thinking and redefine the impossible.
- We are committed to maintaining health, feeding growing populations, and slowing the rate of climate change.
Equal Opportunity
- 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.