(senior) Research Scientist

Description:

The Computational Drug Discovery team is looking for a Research Scientist - Protein Representations. You will have the opportunity to contribute to Owkin’s biopharma endeavors by using and developing state-of-the-art methods for protein representation and optimization. You will be involved in internal R&D projects using both machine learning expertise and domain knowledge.

In this role, you will support our internal drug discovery programs, as well as develop new machine learning algorithms to accelerate those activities.

You will work in R&Tech, under the supervision of the Computational Drug Discovery team lead.

In Particular, You Will
 

• Bring state-of-the-art protein langage models to Owkin
• Develop ML libraries & workflows for protein design
• Develop methods combining 3D structure and sequence to solve tasks relevant to Owkin
• Help develop tools for target assessment
• Support our internal drug discovery pipeline
• Write scientific papers and project reports, participate in scientific conferences
• Participate in our internal R&D, striving to keep Owkin’s methodology to the state-of-the-art
   

About You

Above all, you should be excited by the idea of working at the intersection of drug discovery and machine learning.

The successful candidate will have a ‘team-first’ kind of attitude; be independent, curious and detail-attentive; thrive in a dynamic, fast-paced environment; and be fun to work with.

In terms of skill set, we are looking for someone with:
 

• MSc/engineering degree with a few years of relevant research experience; or PhD in Computational Chemistry, Machine Learning, (Bio)Physics, Mathematics, Statistics or related fields.
• Demonstrated expertise in protein language models and/or the application of 3D-aware models to protein representation (point cloud, 3D GNNs, etc.) including publications at top conferences and journals,
• Strong programming skills in Python with good software engineering skills.
• Knowledge and experience with machine learning toolkits and concepts (scikit-learn, classical algorithms, cross-validation, statistical tests, …). Hands-on experience with deep learning frameworks (Tensorflow, PyTorch, etc.).
• Working biochemistry knowledge, experience working with protein or biologics data (both sequence and structure).
• General knowledge of the drug discovery process, constraints and timelines.
• Excellent written and oral communication skills. Fluent in English.
• Comfortable working in cross-disciplinary teams, highly organized, capable of tackling complex problems logically and effectively, self-driven.