Postdoc Computational science for energy materials (X/F/M)

Postdoc Computational science for energy materials (X/F/M)
Postdoc Computational science for energy materials (X/F/M)

Published	Deadline	Location
today	5 May	Eindhoven

Have you recently completed a PhD in computational science and are you looking for a Postdoc position?
Job description
The Autonomous Energy Materials Discovery Research Group at DIFFER is looking to immediately fill a postdoctoral research position for a four-year term. The successful candidate will play a role in various computational research projects focused on materials and processes for chemical energy.
We are in search of an outstanding junior candidate for this position, who has recently completed their PhD in computational science. The ideal applicant will have a relevant record of scientific achievements and be prepared to engage in a research initiative focused on addressing scientific and technological challenges. The primary technical responsibility of the candidate will be to create and apply generative machine-learning models for the inverse design of nanomaterials used in electrochemical conversion.
This role offers the chance to work alongside a dynamic international team of researchers, contributing to sustainable energy advancements. Therefore, we value a readiness to work together with our industrial partners in turning technological innovations into commercially successful products.
Specifications

• max. 40 hours per week
• Eindhoven View on Google Maps

DIFFER

Requirements
Responsibilities and tasks:

Contribute to a cutting-edge computational research program in alignment with DIFFER's strategic mission.

Use Generative AI in materials science for energy applications, which involves employing deep learning frameworks to create novel material compositions and structures.

Contribute to research proposal development activities.

Daily supervision of intern researchers and PhD candidates.

Disseminate research findings through peer-reviewed publications and conference presentations.

Required skills:

PhD in Computational Science/Engineering, Applied Physics, Chemistry, Materials Science, or a related field, preferably with a focus on AI-driven research.

Track record of high-quality research output.

Experience in developing code using Python.

Experience in using predictive and/or generative machine-learning models.

Collaborative skills and ability to work in an interdisciplinary team.

Fluency in English.

Conditions of employment
This position is for 1 FTE, will be for a period of 4 years and is graded in pay scale 10. The position will be based at DIFFER (www.differ.nl ) and the working location will be at TU Eindhoven. 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/ )
Employer
Dutch Institute for Fundamental Energy Research
The Dutch Institute for Fundamental Energy Research (DIFFER) performs leading fundamental research on materials, processes, and systems for a global sustainable energy infrastructure. We work in close partnership with (inter)national academia and industry. Our user facilities are open to industry and university researchers. As an institute of the Dutch Research Council (NWO) DIFFER plays a key role in fundamental research for the energy transition.
We use a multidisciplinary approach applicable on two key areas, solar fuels for the conversion and storage of renewable energy and nuclear fusion – as a clean source of energy.
Additional information
For more information concerning the position please contact Suleyman Er via [email protected]. To apply for this position, please click the button underneath:

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