The Postdoctoral Fellow will lead research in high-throughput synthesis and discovery of advanced functional materials, with a preferred background in electrocatalysis or battery-related systems. This role supports TMI's mission to accelerate materials innovation through data-driven approaches and autonomous experimentation. The Postdoctoral Fellow will contribute to the rapid exploration of novel materials chemistries—such as compositionally complex energy materials—using high-throughput, combinatorial synthesis strategies. The position involves working at the intersection of robotic synthesis, AI-guided materials discovery, and rapid characterization to enable efficient screening and optimization of functional materials. The Postdoctoral Fellow will collaborate with a multidisciplinary team of researchers and help establish TMI as a leader in autonomous materials research and intelligent laboratory systems.
Responsibilities include developing and optimizing high-throughput and combinatorial synthesis workflows, designing and executing automated synthesis experiments using robotic platforms or parallel reactors, collaborating with computational scientists to integrate machine-learning models for closed-loop materials discovery, and collaborating with companion postdocs on functional materials characterization.
Required qualifications include a Ph.D. in Materials Science, Engineering, Physics, Chemistry, or a closely related field, conferred within three (3) years before the start date of the appointment, demonstrated experience conducting independent research in a relevant area of materials science or engineering, a strong publication record in peer-reviewed journals, excellent written and verbal communication skills, ability to work collaboratively in an interdisciplinary research environment, and commitment to mentoring and contributing to the academic development of graduate and undergraduate students.
Preferred qualifications include experience with materials synthesis, robotic platforms, liquid-handling automation, or programmable synthesis systems, familiarity with machine-learning tools, data analysis, and background in energy materials, catalysis, and batteries.
Salary: $61,093
Working conditions may include working around standard office conditions, repetitive use of a keyboard at a workstation, and use of manual dexterity.
Required materials include a resume/CV, letter of interest, and 3 work references with their contact information; at least one reference should be from a supervisor.
Tagged as: Life Sciences
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