(Senior) Research Scientist - Computational Chemistry

About the role

You’ll be adding to the Drug Discovery Team within our R&Tech department. This team is under the leadership of Floriane, who fosters a culture of innovation, creativity, and teamwork. She is passionate about empowering team members and driving meaningful progress in our drug discovery efforts.

As (Senior) Research Scientist - Computational Chemistry, you will have the opportunity to contribute to Owkin’s biopharma endeavors by using and developing state-of-the-art methods for our drug discovery projects.

In particular, you will support our internal drug discovery and in-licensing programs, as well as develop new methods to accelerate those activities.

In particular, you will:

• Help validate the druggability of our candidate targets
• Perform virtual screening experiments
• Understand SAR from medicinal chemistry papers, competitor’s patents, and internal data
• Support hit prioritization, hit-to-lead and lead optimization stages
• Support our internal method development
• 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 (or equivalent) with at least 3 years of relevant research experience in pharmaceutical/biotech or AI biotech environments; or PhD in Computational Chemistry, Machine Learning, (Bio)Physics, Mathematics, Statistics or related fields. 
• Demonstrated expertise in computational chemistry approaches (docking, molecular dynamics simulations, protein modeling, virtual screening, pharmacophore modeling, etc.) applied to drug discovery programmes in different target families
• Programming skills in Python 
• Working knowledge of cheminformatics including experience working with RDKit
• Knowledge and experience with machine learning toolkits and concepts (scikit-learn, classical algorithms, cross-validation, statistical tests, …)
• Working biochemistry and medicinal chemistry knowledge, experience working with bioactivity data (public, CRO and in-house).
• Strong 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.

Ways to Stand Out

We would be especially excited to read about your:

• Experience in project support in a pharma drug discovery setting
• Experience working on multiple modalities (small molecules, peptides, PROTACs, molecular glues, antibodies, etc.)
• Experience with state-of-the-art ML approaches around molecular optimization, retrosynthesis prediction, ML-based docking, or ML-based protein folding
• Experience with molecular property prediction (ADMET, bioactivity) or generative models for small molecules
• Previous experience with drug discovery data management systems and compound registration (assay databases, electronic lab notebooks, etc.)

For Internal Use: #LI-CJI