PhD Position: Agentic AI-Driven Experiments for Materials Discovery

DIFFER; Netherlands; On-site; EUR 35,000 - 45,000; Full time

Job summary

DIFFER Research in Eindhoven seeks a PhD candidate to join the AMD group, building an agentic AI workflow that converts AI-suggested alloy compositions into executable synthesis and analysis plans. You will work with researchers and industry partners, both in lab automation and data pipelines, to create structured evidence for model development.

The role blends digital workflow development with substantial bench work—about one third digital, two thirds experimental—while training and support are

Qualifications

• Master's degree in CS/AI/related field.
• Strong Python skills and software-engineering practice (Git, testing, reproducible code).
• Experience or interest in agentic AI systems, data pipelines or tool use.
• Willingness to work in a lab and collaborate across disciplines.
• Nice to have lab automation or image/spectral data analysis.

Responsibilities

• Design and run an agentic AI-driven experimental workflow translating AI-proposed compositions into synthesis/characterization plans.
• Carry out high-throughput synthesis of material libraries.
• Characterize samples with micro-XRF and SEM; develop Python pipelines to extract metrics.
• Develop and maintain a FAIR-aligned dataset including realizability labels.
• Connect AI agents to data, planning and reporting tools for traceability.
• Write well-tested software, contribute to publications and complete a PhD within four years.

Skills

Python

Agentic AI

Git

Testing

Reproducible code

Lab automation

English

Multidisciplinary teamwork

Education

Master's degree in computer science

Master's degree in AI/data science

Tools

Python pipelines

Job description

Organisation/Company DIFFER Research Field Computer science » Programming Engineering » Materials engineering Researcher Profile First Stage Researcher (R1) Application Deadline 25 Oct 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

PhD candidate who will join the Autonomous Energy Materials Discovery (AMD) group at DIFFER, working with researchers and engineers who are developing autonomous laboratory technologies. The project is carried out in close collaboration with an industrial partner developing generative AI for materials discovery. The position suits a candidate with strong programming skills, from computer science, AI, physics, chemistry or materials science, who wants to work at the interface of agentic AI, laboratory automation and materials science, and who is happy to spend a substantial part of the project in the lab. Roughly one third of your time will go to the digital workflow and two thirds to experimental work. Training and technical support are provided for all instruments. AI methods can propose material candidates far faster than they can be synthesized and validated. You will help close this gap by building an agentic AI workflow that turns AI-proposed alloy compositions into executable synthesis and characterization plans, and by generating the experimental evidence that shows which candidates can actually be made. You will produce material libraries with a high-throughput nanoparticle printer and characterise them with micro-XRF and SEM. Successful, partial and failed outcomes will be captured in a structured, machine readable dataset to support AI model development and give feedback on material realizability.

In this position, you will have the following responsibilities:

• Design, implement, test and operate an agentic AI-driven experimental workflow that translates AI-proposed compositions into synthesis and characterization plans, supporting quality control, traceability and structured reporting.
• Carry out high-throughput synthesis of material libraries with a nanoparticle printer, with systematic control of composition and deposition conditions.
• Characterize samples with micro-XRF composition mapping and SEM, and develop reproducible Python pipelines to extract composition, homogeneity and morphology metrics.
• Develop and maintain a structured, FAIR-aligned dataset of successful, partial and negative outcomes, including realizability labels, and use it to support AI model development.
• Connect the AI agents to the project's data, planning and reporting steps, including databases and analysis tools, so that the path from candidate selection to validated results is traceable and reproducible.
• 6.Write well-tested, reproducible research software, contribute to publications and conferences, and complete and defend a PhD thesis within four years.

To fulfill the responsibilities listed above, we are looking for a candidate who meets the following requirements:

• A Master's degree in computer science, artificial intelligence, data science, physics, chemistry, materials science, or a related field.
• Strong Python skills and good software-engineering practice, including Git, testing and reproducible code.
• Experience or a strong interest with agentic AI systems, for example LLM-based agents with tool use, workflow automation, or integration with databases and data pipelines.
• Motivation to apply AI in a laboratory setting and willingness to learn hands‑on materials synthesis and characterisation. Prior experience with laboratory instrumentation (e.g. nanoparticle printer, micro-XRF, SEM) is not required.
• Experience with laboratory automation, instrument control, or image and spectral data analysis is an advantage.
• A hands‑on, meticulous working style, good command of English, and the ability to work effectively in a multidisciplinary team.

Additional Information

This position is for 1 FTE, will be for a period of 4 years and is graded in pay scale 19. The starting salary is €3.115,- increasing to €3.989,- in the fourth year of the PhD position. The expected starting date is January 1, 2027.

The position will be based at DIFFER ( www.differ.nl ), Eindhoven, The Netherlands. When fulfilling a position at DIFFER, you will have an employee status at NWO. You can participate in all the employee benefits NWO offers. We have a number of regulations that support employees in finding a good work-life balance. At DIFFER we believe that a workforce diverse in gender, age and cultural background is key to performing excellent research. We therefore strongly encourage everyone to apply.

More information on working at NWO can be found at the NWO website ( https://www.nwo-i.nl/en/working-at-nwo-i/jobsatnwoi/ ).