Machine Learning Research Scientist
Machine Learning Research Scientist

Machine Learning Research Scientist

Full-Time 36000 - 60000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead groundbreaking ML research to revolutionise drug discovery and collaborate with diverse teams.
  • Company: Valence Labs, a pioneering AI research engine focused on transforming medicine development.
  • Benefits: Inclusive culture, competitive salary, and opportunities for impactful research and collaboration.
  • Why this job: Make a real difference in healthcare by advancing machine learning in drug discovery.
  • Qualifications: PhD or equivalent experience in ML applied to drug discovery and strong interdisciplinary collaboration skills.
  • Other info: Join a passionate team dedicated to pushing the boundaries of science and technology.

The predicted salary is between 36000 - 60000 £ per year.

About Valence Labs

Valence Labs is Recursion’s frontier AI research engine. We lead high-impact research programs designed to materially expand Recursion’s ability to discover and develop medicines for complex diseases. Our team balances near-term pragmatism with a long-term view of where the field is heading in the next 3–5 years, incubating, designing, and productizing the approaches we believe will define the future of drug discovery. Our work is driven by optimism, purpose, and a shared vision for a healthier tomorrow. We publish in top journals and conferences, contribute to open science, and engage with some of the world’s most active ML-for-drug-discovery research communities. Our teams are based in London and Montreal, with deep ties to Mila, the world’s largest deep-learning research institute.

About The Role

We’re seeking an experienced ML Research Scientist to drive bold, ambitious research agendas across Valence Labs’ primary research programs, including multi-omic foundation models, next-generation structural biology and atomistic modeling, and approaches for autonomous science. We’re looking for individuals who can articulate and execute a research vision, lead long-running technical projects, and work fluidly across disciplines. You’ll combine mastery of modern machine learning with strong scientific intuition and exceptional engineering skills to develop AI systems that meaningfully accelerate drug discovery.

In this role, you will:

  • Lead and contribute to frontier research programs in ML for drug discovery, including generative models, multi-omic representation learning, and atomistic/structural modeling.
  • Own a research agenda end-to-end: ideation, implementation, experimentation, evaluation, and deployment in collaboration with Recursion’s platform teams.
  • Collaborate closely with interdisciplinary teams of ML researchers, software engineers, wet-lab scientists, and domain experts to identify high-value research opportunities.
  • Communicate findings internally and externally through talks, publications, blog posts, and conference presentations.
  • Contribute to the broader scientific community through open-source, open-science, and collaboration initiatives.

Location: This position is based in Montreal, Canada or London, UK

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.
  • 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.

Machine Learning Research Scientist employer: Recursion

Valence Labs is an exceptional employer, fostering a collaborative and innovative work culture that prioritises diversity and inclusion. With a strong commitment to employee growth, team members are encouraged to engage in high-impact research while contributing to the broader scientific community. Located in vibrant Montreal or London, employees benefit from deep ties to leading research institutes and the opportunity to work alongside passionate experts in the field of machine learning for drug discovery.
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Contact Detail:

Recursion Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Research Scientist

✨Tip Number 1

Network like a pro! Reach out to people in the industry, attend conferences, and join relevant online communities. Engaging with others can lead to opportunities you might not find on job boards.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, research papers, or any relevant work. This gives potential employers a taste of what you can bring to the table.

✨Tip Number 3

Prepare for interviews by practising common questions and discussing your past experiences. Be ready to explain your research vision and how it aligns with the company's goals.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.

We think you need these skills to ace Machine Learning Research Scientist

Machine Learning
Generative Models
Multi-Omic Representation Learning
Atomistic Modeling
Research Vision Articulation
Technical Project Leadership
Interdisciplinary Collaboration
Scientific Knowledge in Biology, Chemistry, or Physics
Neural Network Design
Rapid Prototyping of ML Models
Project Supervision
Publication in Peer-Reviewed Conferences
Open-Source Contribution
Communication Skills

Some tips for your application 🫡

Show Your Passion: When writing your application, let your enthusiasm for machine learning and drug discovery shine through. We want to see that you’re not just qualified, but genuinely excited about the work we do at Valence Labs.

Tailor Your CV: Make sure your CV is tailored to highlight relevant experience in ML research and interdisciplinary collaboration. We love seeing how your unique background aligns with our mission, so don’t hold back on showcasing your achievements!

Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for this role. Be specific about your research vision and how it aligns with our goals. We appreciate clarity and passion, so keep it engaging!

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at Valence Labs!

How to prepare for a job interview at Recursion

✨Know Your Research Inside Out

Before the interview, dive deep into your past research and be ready to discuss it in detail. Valence Labs is looking for someone who can articulate their research vision clearly, so prepare to explain your methodologies, findings, and how they relate to drug discovery.

✨Showcase Your Collaboration Skills

Since this role involves working with interdisciplinary teams, think of examples where you've successfully collaborated with others. Be ready to share how you’ve worked alongside wet-lab scientists or software engineers, as this will demonstrate your ability to thrive in a cross-functional environment.

✨Prepare for Technical Questions

Expect to face technical questions related to machine learning and its application in drug discovery. Brush up on generative models, multi-omic representation learning, and atomistic modeling. Being able to discuss these topics confidently will show that you’re well-prepared for the challenges of the role.

✨Communicate Your Vision

Valence Labs values a long-term view of research. Be prepared to discuss your vision for the future of ML in drug discovery. Think about how your ideas align with their mission and be ready to share how you plan to contribute to their ambitious research agendas.

Machine Learning Research Scientist
Recursion

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