Senior Research Scientist
4 weeks ago
About Valence Labs
Valence Labs is a research and productization engine within Recursion dedicated to advancing the frontier of AI in drug discovery. Combining the intellectual freedom of academia with the resources and stability of industry, we develop novel AI technologies to spearhead a fundamental shift in the way we discover and develop treatments for complex disease. Our research is driven by optimism, purpose, and a shared vision for a healthier tomorrow. We publish in top journals and conferences, are deeply committed to open-science and open-source, and maintain some of the largest and most active research communities in our industry. Our team is headquartered in Montreal, where we share close connections with Mila, the world’s largest deep learning research institute.
About the role
We’re seeking an experienced Research Scientist to pursue bold and high-risk research endeavors supporting our mission of industrializing scientific discovery to radically improve lives. We’re… looking for individuals who possess the ability to own, pursue, and communicate a research agenda, including carrying out long-running projects independently or in a team. This multifaceted role combines the need for a deep understanding of state-of-the-art machine learning algorithms, exceptional problem-solving and engineering skills, and experience in the computational life sciences. In this role, you will:
• Join a Valence Labs Research Unit focused on building AI models for atomistic systems, and contribute to ambitious frontier research within the domain of ML for drug discovery.
• Lead new research projects at the intersection of ML and drug discovery, leveraging your extensive expertise to devise, evaluate, and help deploy innovative and field-leading ML solutions.
• Collaborate with researchers and engineers both internally and externally to identify unique challenges and opportunities for ML in drug discovery.
• Work in a highly supportive, interdisciplinary environment, providing the intellectual freedom of academia with the resources and stability of industry.
• Present and communicate research findings through talks, blog posts, publications, and conferences.
Location: This position is based in Montreal, Québec, Canada
A successful candidate will have most of the following:
• PhD (or equivalent) with significant academic or industry research experience in a related technical field involving machine learning applied to drug discovery.
• Scientific knowledge of biology, chemistry, or physics, along with previous experience working in a scientific environment across disciplines.
• A proven track record of impactful machine learning research, including designing new neural networks to model molecular systems, proposing new theories, improving upon existing ideas, and applying novel ML techniques to real-world problems.
• Advance practical and theoretical knowledge of Quantum Mechanics (QM), molecular mechanics (MM), and Neural Network Potentials (NNP) methods.
• Knowledge of various sampling methods associated with molecular dynamics and quantum mechanical calculations.
• Strong technical and engineering skills, including ability to rapidly prototype ML models.
• Comfort working cross-functionally with interdisciplinary teams of dry and wet scientists.
• Experience in project supervision, leadership, or management, including lead authorship in publications at peer-reviewed conferences (e.g., NeurIPS, ICML, or ICLR) and/or journals (e.g. Nature, Science, JACS, or ACS).
Valence Labs is committed to creating a diverse and inclusive environment, where understanding and accommodating personal needs and preferences is a priority. Join our multidisciplinary team of passionate researchers, eager to push the boundaries of ML research and contribute to industrializing scientific discovery to radically improve lives.
#LI-EP1
Company:Valence Labs
Qualifications: Language requirements: Specific requirements: Educational level: Level of experience (years):Senior (5+ years of experience)
Tagged as: Academia , Machine Learning , Neural Networks , NLP , United Kingdom
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