Sanofi Jobs

A new perspective. A new challenge. A new opportunity.

Job Information

Sanofi Group Computational Biology Scientist, Machine Learning in Large Molecule Research in Framingham, Massachusetts

About the Company:

Every day, Sanofi's 100,000 employees are committed to improve the lives of people around the world, with sustainable and responsible solutions and initiatives. Sanofi is recognized as one of the leading biopharmaceutical companies in the world and is pioneering innovation in biologics with the first approved nanobody drug, the first clinical stage tri-specific antibody, and a novel genetic codon expansion platform for new engineering capabilities. Details of the organization and the company’s mission and goals can be found on our website ( http://www.sanofi.us/l/us/en/index.jsp ).

Overview:

Sanofi Large Molecule Research Platform is opening a new scientist/senior scientist role to seek a computational biologist with strong expertise in computational biology, bioinformatics, artificial intelligence (AI), machine learning (ML), and deep learning (DL). The successful candidate will work in an interdisciplinary team to apply cutting-edge computation, AI/ML/DL, and structural biology technologiesto resolve challenges in real-world drug discovery and make impacts to patients’ life. This is an exciting opportunity to contribute to the process of design and engineering revolutionary biologics, including multivalent, multi-targeting molecules by leveraging proprietary data coming from our industry-leading high-throughput automation platforms. The successful candidate will gain deeper insight into drug development process and transform AI/ML algorithms into accelerating biologics discovery and development process.

Your responsibilities include:

  • Evaluate and develop state-of-the-art computational methods to decode biophysical and geometrical features from antibody-antigen datasets and create predictive models for engineering.

  • Develop and apply complex machine/deep learning solutions to our high-content and high-quality proprietary datasets, as well as public datasets.

  • Perform data querying and feature extraction to improve current workflow for antibody/nanobody engineering, including affinity modification, cross-reactivity engineering, liability risk prediction and mitigation, multi-specific antibody engineering, and de novo antibody design.

  • Maintain a keen awareness of recent developments in data science, bioinformatics, and state-of-the-art of AI/ML/DL algorithms, aiming to accelerate development of new computational algorithms.

  • Effectively collaborate with colleagues with diverse scientific background, identify problems and opportunities, combine computational and structural analysis to support large molecule projects.

Basic qualifications:

  • MS with 5+ years’ or Ph. D. with 0-5 years’ experience in computational structural biology, bioinformatics, computational chemistry, or computational physics, with significant experience in data science and machine learning.

  • Understanding of protein structure and protein-protein interaction. Hands-on experience with structural analysis and optimization of biochemical and biophysical properties, like thermodynamics, with protein design tools e.g. Rosetta, BioLuminate, or MOE, etc.

  • Strong familiarity with core concepts in Deep Learning and Neural Networks including CNNs, RNNs, Embeddings, Transfer Learning, Attention-based Networks, Statistical Learning.

  • Familiarity with deep learning libraries such as Keras, TensorFlow, PyTorch, and bioinformatics pipelines

  • Experience of developing computational prediction models for protein engineering through programming with Python, Shell, or SVL, etc. Experience with cloud computing, parallel computing, and/or supercomputing is expected.

  • Familiarity with protein structure or sequence featurization and learned embeddings. Experience with database mining, big data, and large-scale virtual screening using Bayesian optimization etc is desired.

  • Familiarity with Data Visualization tools/libraries and dimensionality reduction algorithms.

Preferred qualifications:

  • Understanding of biologics R&D process is a plus.

Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.

#GD-SA

#LI-SA

At Sanofi diversity and inclusion is foundational to how we operate and embedded in our Core Values. We recognize to truly tap into the richness diversity brings we must lead with inclusion and have a workplace where those differences can thrive and be leveraged to empower the lives of our colleagues, patients and customers. We respect and celebrate the diversity of our people, their backgrounds and experiences and provide equal opportunity for all.

DirectEmployers