University of California, Berkeley
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3 days ago
Postdoctoral Fellowship in AI, Advanced Materials, and Planetary Health at UC Berkeley BIDMaP University of California, Berkeley in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Starting salary is $85,000/year. The fellowship is a full-time, fixed-term postdoctoral appointment for an initial 2-year term, renewable for a 3rd year upon mutual agreement.
Deadline
Dec 1, 2026
Country
United States
University
University of California, Berkeley

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About this position
Postdoctoral Fellowship in AI, machine learning, data science, advanced materials, and planetary health at the Bakar Institute of Digital Materials for the Planet (BIDMaP), University of California, Berkeley.
This fellowship sits at the intersection of computational discovery science and the physical sciences, with a mission to apply AI/ML and data-driven methods to climate and planetary challenges. The program welcomes recent PhDs from quantitative backgrounds such as AI/ML, computer science, statistics, or data science, as well as domain scientists from chemistry, physics, biological sciences, or materials science who want to integrate machine learning into discovery workflows.
Location: Berkeley, California, United States.
Funding: Starting salary is $85,000/year. The appointment is full time, fixed term, initially for 2 years and renewable for a 3rd year by mutual agreement.
Eligibility: Applicants must hold a PhD or equivalent degree awarded between January 2025 and August 2027.
Timeline: Applications open October 15, 2026. Full consideration deadline is December 1, 2026, and review continues until all fellowships are filled. Target start date is Spring/Summer 2027.
How to apply: Submit an application through the linked Nature Careers posting / application portal. Review the posting carefully for the external application steps.
Funding details
Starting salary is $85,000/year. The fellowship is a full-time, fixed-term postdoctoral appointment for an initial 2-year term, renewable for a 3rd year upon mutual agreement.
What's required
Applicants should hold a PhD or equivalent degree awarded between January 2025 and August 2027. Preferred backgrounds include advanced training in AI/ML, computer science, statistics, or data science with a strong drive to apply computational methods to physical science problems, or advanced training in chemistry, physics, biological sciences, or materials science with a strong vision for integrating AI/machine learning into discovery workflows.
How to apply
Apply on the website linked in the posting. Applications open October 15, 2026 and are considered for full review by December 1, 2026; review continues until all fellowships are filled.
More information can be found here
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