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Valence Labs

Valence Labs

www.valencelabs.ca

3 Jobs

51 Employees

About the Company


Valence Labs is Recursion's AI research engine. Leveraging the full power of Recursion's platform, data, and computing infrastructure, we develop new ways to predict, explain, and ultimately decode biology.

Listed Jobs

Company background Company brand
Company Name
Valence Labs
Job Title
Machine Learning Research ScientistNew
Job Description
**Job Title** Machine Learning Research Scientist – Drug Discovery **Role Summary** Lead pioneering machine‑learning research to accelerate drug discovery. Own end‑to‑end research initiatives, from hypothesis to deployment, and collaborate with multidisciplinary teams of scientists and engineers. Deliver high‑impact publications and maintain active engagement with the broader ML research community. **Expectations** - Drive the research agenda for frontier ML applications in drug discovery, including generative models, multi‑omic representation learning, and atomistic/structural modeling. - Produce reproducible, publishable results and contribute to open‑science initiatives. - Mentor junior researchers and manage project timelines within a cross‑functional environment. **Key Responsibilities** - Design, implement, and evaluate novel neural network architectures for modeling biological, chemical, and physical systems. - Lead long‑running technical projects: ideation, algorithm development, experimentation, benchmarking, and deployment with platform teams. - Collaborate closely with wet‑lab scientists, software engineers, and other ML researchers to translate scientific challenges into machine‑learning solutions. - Present findings internally and externally via talks, papers, blog posts, and conference presentations. - Maintain code‑base quality, documentation, and reproducibility standards; contribute to open‑source releases. - Engage with academic and industry communities, co‑authoring publications in top journals and conferences. **Required Skills** - Advanced expertise in machine‑learning techniques: generative modeling, representation learning, and physics‑informed neural networks. - Strong programming and engineering skills; rapid prototyping in Python (TensorFlow/PyTorch). - Experience with multi‑modal biological/chemical/physical data and atomistic simulations. - Proven ability to lead interdisciplinary projects, manage timelines, and mentor collaborators. - Excellent written and verbal communication for scientific outreach and collaboration. - Familiarity with open‑science practices, reproducible research workflows, and community standards. **Required Education & Certifications** - Ph.D. or equivalent in machine learning, computational biology, chemistry, physics, or a closely related technical field. - Demonstrated research record with first‑author or lead‑author publications in peer‑reviewed venues (e.g., NeurIPS, ICML, ICLR, Nature, Science, JACS, or ACS). - Experience applying ML methods to real‑world drug‑discovery problems, including development of new neural network architectures or modeling techniques.
London, United kingdom
Hybrid
03-12-2025
Company background Company brand
Company Name
Valence Labs
Job Title
ML Intern, Research
Job Description
Job title: ML Intern, Research Role Summary: Assist in advancing AI-driven drug discovery by designing, implementing, and deploying novel machine learning methods for multi‑omic models, structural biology, and autonomous science. Collaborate with interdisciplinary scientists to translate research findings into scalable ML systems. Expactations: - Enrollment in a post‑doctoral, PhD, or Master’s program. - Strong programming and modern software engineering practices, especially in Python. - Experience building high‑performance deep‑learning implementations and deploying them at scale. - Proven ability in designing architectures, experimentation, analysis, and deployment. - Solid foundation in linear algebra, calculus, and statistics with a passion for real‑world ML applications. Key Responsibilities: - Develop and refine ML approaches to accelerate drug discovery pipelines. - Build and maintain distributed machine‑learning platforms that handle large‑scale biological data. - Work closely with wet‑lab and dry‑lab teams to incorporate experimental insights into models. - Produce technical documentation, presentations, blog posts, and conference papers. - Contribute to codebases, ensuring reproducibility and performance optimizations. Required Skills: - Advanced proficiency in Python and related ML libraries (PyTorch, TensorFlow). - Deep‑learning training, tuning, and deployment experience on distributed systems. - Strong data engineering and scientific computing skills. - Ability to read and implement methodologies described in academic literature. - Excellent communication skills for presenting complex results. Required Education & Certifications: - Current enrollment in a post‑doctoral fellowship, PhD, or Master’s degree in Computer Science, Machine Learning, Bioinformatics, Computational Biology, or related fields. - (Optional) Authorship in peer‑reviewed ML conferences (NeurIPS, ICML, ICLR).
Montréal-ouest, Canada
Hybrid
Fresher
16-01-2026
Company background Company brand
Company Name
Valence Labs
Job Title
Machine Learning Research Scientist
Job Description
Job title: Machine Learning Research Scientist Role Summary Spearhead cutting‑edge research in machine learning for drug discovery, focusing on generative models, multi‑omic representation learning, and atomistic/structural modeling. Own project lifecycle from ideation to deployment, and collaborate across computational, experimental, and chemical disciplines to accelerate therapeutic discovery. Expectations - Design, implement, and evaluate novel ML algorithms that advance drug discovery. - Drive the full research cycle: hypothesis formation, model building, experimentation, and real‑world deployment. - Lead interdisciplinary teams, influence project direction, and ensure deliverables meet scientific and engineering standards. - Produce high‑impact publications and communicate findings via talks, blogs, and conferences. - Champion open‑science initiatives and contribute to community resources. Key Responsibilities - Lead frontier research programs in ML for drug discovery (generative models, multi‑omic foundations, atomistic modeling). - Own end‑to‑end research agenda: ideation, implementation, experimentation, evaluation, and production deployment. - Collaborate with ML researchers, software engineers, wet‑lab scientists, and domain experts to identify high‑impact opportunities. - Publish papers in top-tier conferences (NeurIPS, ICML, ICLR) and journals (Nature, Science, JACS, ACS). - Present research internally and externally through talks, papers, blogs, and conferences. - Contribute to open‑source projects and broader scientific community. - Mentor junior researchers and guide cross‑disciplinary project execution. Required Skills - Proficiency in modern deep learning frameworks (PyTorch, TensorFlow). - Experience with generative modeling, multi‑modal representation learning, and atomistic/structural modeling. - Strong programming and rapid prototyping abilities. - Ability to translate complex scientific problems into ML solutions. - Excellent written and verbal communication skills. - Proven ability to work effectively in interdisciplinary, cross‑functional teams. - Leadership experience in research projects, including publication lead authorship. Required Education & Certifications - PhD or equivalent in Machine Learning, Computational Biology, Chemistry, Physics, or related field. - Significant academic or industry research experience in ML applied to drug discovery.
Montréal-ouest, Canada
Hybrid
20-01-2026