Senior Group Leader, Valence Labs
6 months ago
**About Valence Labs**
Valence Labs is an AI research and productization engine within Recursion dedicated to industrializing scientific discovery to radically improve lives. Combining the intellectual freedom of academia with the resources and stability of industry, our focus is the development of highly-autonomous systems that will spearhead a fundamental shift in the way treatments are discovered and developed 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 located in London and Montreal, where we share close connections with Mila, the world's largest deep learning research institute.
**About the role**
We're seeking an experienced Group Leader to lead, mentor, and grow a new scientific team of its own in the pursuit of 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 leadership ability to create, staff, execute, and clearly communicate a research agenda, including carrying out long-running cross-functional projects within their team and in collaboration with external research groups. This multifaceted role requires exceptional communication and problem-solving skills, as well as experience in the computational life sciences. In this role, you will:
- Join Valence Labs' leadership as the head of your research unit, driving ambitious frontier research within the domain of autonomous scientific discovery and ML for drug discovery.
- Work in a highly supportive, interdisciplinary environment, providing the intellectual freedom of academia with the resources and stability of industry.
- Lead new research projects at the frontier of your field of research to devise, evaluate, and help deploy innovative and field-leading ML solutions.
- Collaborate and leverage the current expertise of Valence Labs research units's to achieve high-value collaborative research. Key research areas currently include: causal inference and active learning, multi-modal representation learning for biological and chemical entities, and machine learning for simulation of atomistic systems.
- Be accountable for fostering the creativity of your research team while keeping alignment with Valence's vision of creating highly autonomous systems capable of Nobel-worthy insights to unlock a second scientific revolution.
- Be responsible for the growth and mentorship of the scientists within your team.
- Present and communicate research findings through talks, blog posts, publications, and conferences.
- PhD with significant academic and industry research experience in a related field.
- Experience in project supervision, leadership, and management. Including 4 years of industry experience or similar (e.g. assistant professor).
- A proven track record of impactful machine learning research, particularly in the fields of life sciences or drug discovery as demonstrated by lead authorship in publications at peer-reviewed conferences (e.g., NeurIPS, ICML, or ICLR) or journals (e.g. Nature, Science, JACS, or ACS).
- Strong technical and engineering skills, including the ability to rapidly prototype ML solutions.
- Comfort working cross-functionally with interdisciplinary teams of dry and wet scientists.
**Nice to have**:
- Scientific knowledge of biology, chemistry, or physics, along with previous experience working in a scientific environment across disciplines.
- Experience in building and deploying high-performance implementations of deep learning algorithms.
- Contribution to high-visibility ML codebases.
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.
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