Senior Machine Learning Research Scientist (m/f/d) - Generative AI for Drug Design

Senior Machine Learning Research Scientist (m/f/d) – Generative AI for Drug Design

Location: Berlin, Germany

Join our pioneering team at the forefront of AI-driven drug discovery. As authors of the FLOWR and PILOT frameworks, we are expanding our group of machine learning research scientists to further advance the development and application of state‑of‑the‑art generative models for both structure‑ and ligand‑based drug design. In this role, you will design, implement, and validate novel machine learning tools that generate testable hypotheses and help accelerate the entire drug discovery continuum.

What You Will Do

• Design, develop, and validate state‑of‑the‑art machine learning models, focusing on generative AI and self‑supervised learning.
• Apply modern generative frameworks (e.g., diffusion or flow‑based approaches) to molecular design challenges.
• Develop predictive models combining structural and biochemical data (e.g., binding affinity prediction).
• Explore and implement novel representation learning approaches using large‑scale, unlabeled datasets.
• Translate emerging research in machine learning into impactful applications in drug discovery.
• Collaborate with cross‑functional experts in computational biology, chemistry, and medicine design.
• Contribute to publications, conferences, and external scientific engagement.

Your Profile

Required Qualifications

• Advanced degree or equivalent experience in Computer Science, Machine Learning, Mathematics, Computational Biology, or a related field.
• Proven experience in developing machine learning models and algorithms.
• Strong programming skills, especially in Python.
• Experience working with scientific or complex structured datasets.

Preferred Qualifications

• Strong publication record in machine learning or computational science (e.g., NeurIPS, ICML, ICLR, or comparable venues).
• Hands‑on experience implementing deep learning models using frameworks such as PyTorch.
• Expertise in modern generative modeling techniques, such as diffusion models, flow‑matching approaches, reinforcement learning, and/or self‑supervised learning methods.
• Experience working with scientific data types relevant to drug discovery (e.g., molecular structures, protein data, or large‑scale biological datasets).
• Experience with high‑performance computing environments (e.g., SLURM) and/or cloud platforms (e.g., AWS, Google Cloud).
• Familiarity with cheminformatics tools (e.g., RDKit).
• Proven ability to translate research ideas into applied solutions in a scientific or industrial setting.

Technologies We Use

Slurm‑based on‑premise compute clusters, Google Cloud Platform, AWS, Docker, Kubernetes, Python (PyTorch, NumPy, pandas, scikit‑learn, RDKit).

Pfizer guarantees equal opportunity throughout the application process and complies with local laws in all countries where Pfizer operates. Pfizer excludes any discriminatory factors such as gender, age, ethnicity, religion, world view, sexual orientation, or disability. Inclusion of people with disabilities: We encourage individuals to showcase their best selves and assure that reasonable accommodations will be made to support their application and future career.