Senior Researcher - Machine Learning - Microsoft Research

Microsoft • Redmond, WA

6d

About The Position

Health Futures is a mission-focused organization within Microsoft Research, working at the forefront of artificial intelligence, healthcare, and life sciences research. We are a global and diverse team of engineers, scientists and domain experts who are working on expanding the technological frontier of health and life sciences through deep research. We offer a unique and vibrant environment that features innovative academic research, enterprise software development, and real-world delivery, with close feedback loops and rapid iterations between all three. Our mission is to empower every person on the planet to live a healthier future.
We are looking for a Senior Researcher - Machine Learning to help us advance the ways artificial intelligence can accelerate and advance discovery in biomedicine and the life sciences. This role is ideal for a candidate with intellectual curiosity who wants to craft a research agenda, articulate it clearly to team members with a diverse set of backgrounds, and execute on it as a member of that research team. Successful applicants will bring deep expertise about AI and will be passionate about making new discoveries in health and the life sciences.
At Microsoft, our mission—to empower every person and every organization on the planet to achieve more—guides how we partner with customers to deliver trusted, impactful solutions. With a growth mindset culture, we innovate responsibly and measure success by shared progress—people, teams, and customers. Join us to do meaningful work that changes the world and helps shape what’s next for everyone.

Requirements

• Doctorate in relevant field
• OR Master's Degree in relevant field AND 3+ years related research experience
• OR Bachelor's Degree in relevant field AND 4+ years related research experience
• OR equivalent experience.

Nice To Haves

• Experience creating and using generative AI or other ML techniques in the life sciences.
• Experience working with biological data (e.g., genomics, transcriptomics, proteomics, microscopy), applying both advanced methods and standard bioinformatics tools. Proven track record in bioinformatic algorithm development, benchmarking, interpretation, and application.
• Experience innovating software, systems, or workflows that leverage generative AI-based systems to solve real-world problems in the life sciences. This includes techniques like context engineering, prompt optimization, and optimization of test-time compute.
• Experience creating robust, repeatable technical research artifacts as part of an interdisciplinary team.
• Experience publishing academic papers as a lead author or essential contributor.

Responsibilities

• Design, implement, and evaluate novel methodologies for scientific discovery through artificial intelligence, non-exhaustively including techniques around post-training, inference-time optimization, interpretability, and experimental design.
• Application-specific benchmarking and interpretation: Invent and apply techniques for developing a deep understanding of the capabilities of deep learning models as they relate to specific biological data domains and life sciences research questions of interest.
• System Optimization: Develop approaches for inference-time optimization of interaction patterns with deep learning models, e.g., context optimization, intelligent sampling, etc.
• In addition to these specific technical areas, candidates will be required to participate in robust, repeatable team-based technical research and be effective communicators.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree