Postdoctoral Fellowship in AI, Advanced Materials, and Planetary Health At BIDMaP, UC Berkeley

Bakar Institute of Digital Materials for the Planet (BIDMaP), University of California at Berkeley; Berkeley (CA); Vor Ort; USD 70.000 - 90.000; Vollzeit

Zusammenfassung

BIDMaP at UC Berkeley invites recent PhDs to apply for a Postdoctoral Fellows Program that combines AI, ML, and data science with the physical sciences to address climate change. Applications open October 15, 2026, with a deadline of December 1, 2026 for full consideration and ongoing review until all fellowships are filled.

The target start date is Spring/Summer 2027. Duration is an initial two-year appointment, renewable for a third year upon mutual agreement, located at UC Berkeley in the

Qualifikationen

• PhD or equivalent degree awarded between January 2025 and August 2027.
• Strong background in AI/ML or data science with a focus on applying computational methods to physical science problems.
• Background in chemistry, physics, biology, or materials science is welcomed for integration with discovery workflows.

Kenntnisse

AI/ML background

Data science

Ausbildung

PhD or equivalent degree

Jobbeschreibung

At BIDMaP (Bakar Institute of Digital Materials for the Planet) UC Berkeley, researchers are combining AI, machine learning, and data science with the physical sciences to confront climate change head-on.
BIDMaP’s Postdoctoral Fellows Program invites applications from recent PhDs in basic or data science fields who are passionate about using computation and discovery science to drive planetary solutions.
Applications Open: October 15, 2026
Application Deadline: December 1, 2026 for full consideration, review will continue until all available fellowships are filled
Target Start Date: Spring / Summer 2027
Duration: Initial 2-year appointment, renewable for a 3rd year upon mutual agreement.
Location: BIDMaP is housed in the beautiful new Barbara and Gerson Gateway at UC Berkeley

About You

Candidates should hold a PhD or equivalent degree awarded between January 2025 - August 2027 and have one of the following backgrounds

Quantitative focus:

Advanced training in AI/ML, computer science, statistics, or data science with a strong drive to apply computational methods to physical science problems.

Domain science focus:

Advanced training in chemistry, physics, biological sciences, or materials science with a strong vision for integrating AI/machine learning into discovery workflows.