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Deep Learning Research Scientist – Structural Biology

DeepLife is hiring!

About

DeepLife is a series A startup focused on addressing the urgent need to increase drug discovery reliability by acting on the earliest step, drug target identification. This consists of identifying, a molecular target, such as a protein, that will trigger the transition from disease to healthy cells. With current methods, only 1 target in 10,000 reach the market, leading to a significant loss of time and efforts in the community.

Our approach is to leverage the recent revolution in the omics data, measuring precisely cells activity at large scale, and build foundation models to mimic cell behavior in various contexts and identify the optimal trigger to reverse disease state.

Half of the team today is dedicated to build the largest omics database, aka omics atlas, to map all human body tissues and diseases and reduce experimental biases.

We offer a research friendly environment, with 90% of the company holding a PhD, with academic collaborations and publications. The team is international and composed of +10 different nationalities. The company is remote first with most of the work is remote and regular events organized in our offices in Paris.

Job Description

Overview:

We are seeking a Deep Learning Scientist specializing in structural biology for modeling complex biomolecular interactions. In this pivotal role, you will develop state-of-the-art models to predict protein‑protein, protein‑molecule, and RNA interactions, directly advancing our drug discovery and therapeutic research initiatives. The successful candidate will combine expertise in cutting-edge deep learning techniques with robust structural biology insights to drive breakthrough innovations.

Key Responsibilities:

• Innovative Model Development: Design, implement, and optimize deep learning models that accurately predict protein‑protein, protein‑molecule, and RNA interactions using the latest advancements in deep learning and structural biology.

• Data Integration & Curation: Integrate experimental structural data with computational predictions to enhance model precision and reliability.

• Cross-functional Collaboration: Partner with structural biologists, bioinformaticians, and experimental teams to validate models and translate computational insights into actionable research outcomes.

• Model Benchmarking & Validation: Rigorously assess model performance using state-of-the-art benchmarking techniques and iterate based on new scientific insights.

• Project Leadership: Lead initiatives in computational structural biology, guiding projects from conception to execution while ensuring timely delivery and scientific excellence.

What We’re Looking For:

• Deep expertise in applying state-of-the-art deep learning approaches to structural biology challenges.

• Demonstrated experience in developing predictive models for protein‑protein, protein‑molecule, and RNA interactions.

• A strong track record in integrating experimental structural data with computational techniques to drive innovative solutions.

• Practical industry experience in a dynamic research or biotech setting.

Why Join Us?

Become part of a forward-thinking team where your innovative contributions will directly influence cutting-edge discoveries in biomolecular interactions. Your work will help shape the future of drug discovery and therapeutic development, making a tangible impact on patient outcomes and scientific progress.

Preferred Experience

Qualifications (Ranked from Most Important to Least Important):

• Ph.D. in Computational Biology, Structural Biology, Bioinformatics, or a closely related field with a strong emphasis on deep learning and structural modeling.

• Proven expertise in designing and implementing State of the art deep learning models for predicting protein‑protein, protein‑molecule, and RNA interactions.

• Demonstrated ability to integrate structural biology data with computational modeling strategies.

• Proficiency in programming languages such as Python and familiarity with deep learning frameworks.

• Excellent communication skills, capable of conveying complex scientific concepts to interdisciplinary teams.

• Experience in a fast-paced, innovative R&D environment, with a record of high-impact research publications a plus.

Ready to push the boundaries of computational structural biology? Apply today and join us on our mission to revolutionize drug discovery and therapeutic innovation!

Additional Information

  • Contract Type: Full-Time
  • Location: Paris
  • Possible full remote
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