Nanyang Technological University
1 week ago
Postdoctoral Fellow in AI/ML-Driven High-Throughput Material Synthesis and Characterization Nanyang Technological University in Singapore
Degree Level
Postdoc
Field of study
Computer Science
Funding
Available
Country
Singapore
University
Nanyang Technological University

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About this position
Postdoctoral Fellow opportunity at Nanyang Technological University (NTU), Singapore.
The School of Materials Science and Engineering is recruiting for a postdoctoral researcher to join the collaborative AxCIS Lab – AI xploration of Catalysis with Inorganics and Surfaces programme involving NTU, the National University of Singapore (NUS), and BEARS.
This position focuses on AI/ML-driven high-throughput, closed-loop experimentation for the discovery and optimization of electrocatalytic materials for CO2 reduction. The successful candidate will develop automated materials fabrication and characterization workflows, integrate agentic AI systems for autonomous experimentation, and work on multi-parameter optimization, catalyst structure–performance relationships, and in-situ catalyst regeneration strategies.
The role is highly interdisciplinary and sits at the intersection of materials science, chemistry, chemical engineering, and computer science. The postholder will collaborate with computational researchers and electrochemical characterization researchers, validate predictive models, analyze experimental data, and contribute to publications and conference presentations.
Eligibility highlights: a PhD in Chemistry, Materials Science and Engineering, Chemical Engineering, or a closely related discipline; strong hands-on experience with AI/ML-driven high-throughput experiments; experience in experimental automation and autonomous decision-making workflows; familiarity with machine learning, optimization algorithms, and data-driven materials discovery; and a strong publication record.
Location: Singapore.
Application: Apply via the NTU Workday portal using the official link provided in the post. No deadline is stated in the text.
Funding details
Available
What's required
A PhD degree in Chemistry, Materials Science and Engineering, Chemical Engineering, or a closely related discipline is required. Applicants should have strong hands-on experience in AI/ML-driven high-throughput experiments, preferably in materials science, electrochemistry, or related fields, plus experience developing AI-agentic workflows for experimental automation, data analysis, and autonomous decision-making. Experience with multi-parameter experimental optimization, structure–performance analysis, mechanistic investigations, machine learning techniques, optimization algorithms, and data-driven materials discovery is preferred. A strong publication record, independent research ability, analytical/problem-solving skills, teamwork, mentoring, organization, and strong written and verbal communication skills are expected.
How to apply
Apply through the NTU Workday job portal using the provided application link. Review the full job posting and submit the required application materials online. Only shortlisted candidates will be notified.
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