Job description

Overview 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 for Life Sciences 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 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. #Research 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. Qualifications Required Qualifications • 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. Preferred Qualifications • 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. Research Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: careers.microsoft.com This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Requirements

Must-haves

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.
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.
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Nice-to-haves

Experience creating and using generative AI or other ML techniques in the life sciences.
Experience creating robust, repeatable technical research artifacts as part of an interdisciplinary team.
Experience publishing academic papers as a lead author or essential contributor.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Application prep

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Keywords to mirror

machine learningaiml

Platform: eightfold
Effort: medium

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