Postdoctoral Researcher/Fellow (AI for Energy Materials)

How to use this kit

Ground every answer in facts on this page and the original listing. We never invent Glassdoor-style reviews or salaries that are not in our data.

Interview prep

• Walk through a past paper or project end-to-end: hypothesis, data, model or simulation, failure modes, and what you would redo
• Explain how AI methods map to energy-materials questions (stability, discovery, inverse design) without overclaiming
• Prepare collaboration examples with experimentalists or multi-author teams and a short research agenda for NTU

Fit summary

Strong fit if you want university research in Singapore, publishable AI-for-materials work, and independence under a faculty PI. Weaker fit if you need remote work, industry product delivery pace, or a permanent staff ladder from day one.

Day in the role

As a Postdoctoral Researcher/Fellow (AI for Energy Materials) at NTU, a typical day centers on designing and running ML or simulation experiments on materials problems, reading papers, cleaning and analyzing datasets, writing code and notes for reproducibility, and syncing with PIs and lab collaborators. Expect paper drafts, seminar talks, and grant- or project-milestone updates alongside wet-lab or computational partners depending on the group.

Skills to emphasize

• Deep learning / scientific ML for materials (structure–property, surrogate models)
• Materials informatics, DFT or MD workflow literacy as needed by the group
• Python research stack, experiment tracking, and clear paper writing

FAQ from this listing

Is this role remote?

No. The listing is for Singapore with remote set to off; expect on-campus research.

What does NTU emphasize in this area?

Public research university work with active AI and materials-adjacent collaborations (e.g., AI systems and industry research partnerships in recent news).

Are salary or review scores available here?

No verified salary bands, Glassdoor/Indeed scores, or star ratings were in the provided DATA.

Company facts (cached)

Website: ntu.edu.sg

Nanyang Technological University (NTU) is a national public research university in Singapore. Founded in 1981, it is also the second oldest autonomous university in the country.

Public cache only — not an employee review.

Role overview (listing rewrite)

Postdoctoral Researcher/Fellow (AI for Energy Materials) at Nanyang Technological University, Singapore The Opportunity Nanyang Technological University is seeking a Postdoctoral Researcher/Fellow to join our cutting-edge research team focusing on the intersection of artificial intelligence, computational chemistry, and energy materials. This role will involve developing AI-driven methodologies for catalyst and materials discovery, conducting atomistic simulations, and gaining data-driven insights into complex energy systems. What You'll Do Conduct research at the interface of AI, computational chemistry, and energy materials Develop AI-driven methods for catalyst and materials discovery Perform atomistic simulations to understand material properties and behavior Utilize data-driven approaches to gain insights into complex energy systems Qualifications PhD in Computer Science, Chemistry, Materials Science, or a related field with a focus on AI for materials science Strong background in computational chemistry and/or machine learning Prior experience in AI-driven catalyst and material discovery is preferred Proficiency in programming languages such as Python, R, or MATLAB Experience with molecular dynamics simulations and data analysis tools Working at Nanyang Technological University Nanyang Technological University offers a dynamic research environment and opportunities for collaboration across disciplines. Our commitment to innovation and excellence will provide you with the resources and support needed to advance your career. How to Apply To apply, complete your application directly on this page, or you'll be redirected to the employer's application platform to finish submitting there.

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Questions to ask them

• What does success look like in the first 90 days for this role?
• How is the team structured, and who would I work with most?
• What tools and systems does this role use daily?
• Is the work primarily based in Singapore, hybrid, or fully remote?