Computational Scientist for de novo Protein Design - all genders - Inklusiver Job 🦼 🦻 🦯
- +2
- +7
- Frankfurt, Brandebourg, Germany
- +2
- +7
- Frankfurt, Brandebourg, Germany
À propos
About the job Our Team: Within Large Molecules Research (LMR) we utilize cutting-edge protein engineering technologies for the discovery and optimization of next-generation protein therapeutics. The team has an impressive track record of patents and publications in high-impact journals. You will be a part of our global AI Innovation team which is part of LMR's Digital Biologics Platform (DBxP). As a global organization, we are dedicated to pushing the boundaries of computational and AI-based protein engineering to design innovative new medicines. Main responsibilities: Contribute to the evolution of our computational platform for Antibody/NANOBODY de novo design. Drive the development, training, and integration of novel deep and machine learning-based models for protein design & optimization. Collaborate with interdisciplinary antibody & NANOBODY screening and engineering teams to define strategies for experimental validation of computationally designed variants. Apply our computational workflows for protein design & optimization in portfolio projects to design novel antibody/NANOBODY variants in the context of therapeutically relevant targets. Depending on your skill set, prior experience, and interests, there are opportunities to focus your contribution on specific aspects of the overall workflow (e.g. development of foundational AI-based models, application of computational methods in the context of portfolio projects,...). About you Education and professional Experience Ph. D. degree in the field of computational structural biology or computational life sciences (e.g. bioinformatics, computer science, biophysics, computational biology, data science (AI/ML) or life sciences with strong expertise in AI/ML & computational protein design). Post-doctoral level experience (2-4 years) on de novo protein design of immunoglobulin-like scaffolds. Strong track record in methods for predicting biomolecular complexes (e.g. docking) and computational protein engineering. Experience in the implementation and application of ML-based methods for generative protein design. Strong publication track record in the field of ML-driven immunoglobulin/protein design. Soft skills Passion to collaborate with others, self-development with a focus on scientific know-how, and sharing knowledge. Ability to work both independently and in cross-functional international teams. Technical skills Strong expertise in de novo protein design of immunoglobulin-like (Ig) scaffolds and functionalization studies. Deep understanding on the physical principles that govern protein folding and protein complex formation. Deep expertise in AI/ML-based approaches for protein de novo design including application, training & fine-tuning of generative protein language models, diffusion- and flow matching approaches. Knowledge of antibody/NANOBODY structure, function & engineering. Proven experience on developing and applying computational methods for the prediction of antibody/NANOBODY - antigen interactions (e.g. LightDock, HADDOCK). Proficiency in Python and related libraries/software for de novo design (e.g. RFdiffusion, proteinMPNN, Rosetta, pyRosetta). Ability to develop, benchmark and apply predictive algorithms for protein engineering. Experience in handling, curating, and managing large biological data sets and data bases. Expertise in developing and maintaining data pipelines and automated data workflows. Comfortable working in cloud and high-performance computational environments. Languages: Fluency in English Why choose us? Bring the miracles of science to life alongside a supportive, future-focused team. Discover endless opportunities to grow your talent and drive your career, whether it's through a promotion or lateral move, at home or internationally. Benefit from a well-thought-out benefits package that rewards your contribution and commitment. We take care of you and your family with a wide range of health and social such as high-quality healthcare, numerous prevention programs and coverage for long-term illness. Our 14-week paid family leave for both parents is outstanding as well as a wide range of childcare benefits. Pursue Progress. Discover Extraordinary. Progress doesn't happen without people - people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. You can be one of those people. Chasing change, embracing new ideas and exploring all the opportunities we have to offer. Let's pursue progress. And let's discover extraordinary together. At Sanofi, we provide equal opportunities to all regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity. Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com ! #LI-Hybrid #LargeMoleculesResearch #ArtificialIntelligence #MachineLearing #ProteinEngineering #SanofiCareers #PursueProgress #DiscoverExtraordinary #WeAreSanofi #WeNeverSettle #TeamSanofi #IgnitingPotential Diversity und Inklusion sind in den Grundwerten von Sanofi verankert und spiegeln sich in unserer Arbeitsweise wider. Wir respektieren die Vielfalt unserer Belegschaft in Hinsicht auf ihre Herkunft, Erfahrungen und Lebensweisen. Wir erkennen die Bereicherung, die diese Vielfalt birgt, und fördern Inklusion sowie eine Arbeitsumgebung, in der diese Unterschiede sich weiter entwickeln können, zur Stärkung des Lebens unserer Mitarbeiter, Patienten und Kunden.
Compétences idéales
- Python
- Machine Learning
- Deep Learning
- Cloud Computing
- High Performance Computing
- Bioinformatics
- Data Science
Expérience professionnelle
- Machine Learning
- Data Scientist
Compétences linguistiques
- English