Principal Machine Learning Scientist (all genders)
Indexed description
Your Tasks And Responsibilities
- You lead the development, evaluation, and application of biological foundation models, including protein/RNA language models, single-cell and spatial-omics foundation models, as well as multimodal generative architectures
- You drive the design and implementation of virtual cell and virtual patient models that integrate multi-scale, multimodal biological data to simulate cellular states and enable in-silico patient stratification
- You identify opportunities to accelerate ongoing drug discovery projects through internal and external AI capabilities
- You communicate, educate, and engage with a broad set of stakeholders, including biologists, chemists, computational/data scientists, R&D leadership, consortia partners, and the scientific community
- You keep up to date with the latest advances in biological foundation models, virtual cell/patient modeling, and related fields, publishing and presenting both internally and externally
- You routinely collaborate with colleagues from R&D and occasionally interact with BD&L, industrial partners, and the academic community
- You lead initiatives to integrate AI into biomedical research
- You foster collaboration and knowledge sharing within the team and with external partners
- You 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
- You bring long-term experience in industry and deep expertise with state-of-the-art machine learning methods to model biology, such as sequence-to-function models, nucleotide language models, generative methods, multimodal fusion methods
- You have hands-on experience with ML-based workflows for biomolecular modelling, perturbation-response prediction, gene regulatory network inference, digital twin modeling, or patient-level phenotype prediction from multi-omics data
- You are experienced with large-scale biological datasets such as single-cell/spatial omics, bulk transcriptomics, proteomics, imaging, and integrating heterogeneous data modalities
- You demonstrate strong Python programming skills (e.g. PyTorch, pandas, scikit-learn) and experience in collaborative software engineering according to best practices
- You bring expertise in modern bioinformatics tools and DNA/RNA biology as well as in agentic AI workflow development
- You are committed to scientific rigor, possess excellent analytical thinking skills, are highly self-motivated, and have a proven track record of scientific achievement
- Excellent written and verbal communication skills in English round off your profile
- We ensure your financial stability with a competitive salary between 104.300€ and 126.500€ per year (full-time) plus a variable component. Your compensation is based on your qualifications, skills, and professional experience.
- 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.
- We embrace diversity by providing an inclusive work environment in which you are welcomed, supported, and encouraged to bring your whole self to work.
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: 871306
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