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Postdoc in Machine Learning of Plasma-Assisted D ... (No replies)
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Postdoc in Machine Learning of Plasma-Assisted Deposition Processes
Adviser: Dr. Matthias Rupp (mrupp.info)
Location: Luxembourg Institute of Science and Technology, Esch-sur-Alzette, Luxembourg (list.lu)
Keywords: atomistic machine learning, electronic structure, plasma, vapor deposition
We are looking for a colleague to join the newly established research group "Process Modelling, Automation, and Robotisation" at the Luxembourg Institute of Science and Technology in the Materials Research and Technology department. You will work with Matthias Rupp, the group's leader, and collaborators, such as Prof. Alexandre Tkatchenko at the University of Luxembourg. The position is fully funded (two years).
In the group, we perform state-of-the-art research in machine learning for physics, chemistry, and materials science. For this, we combine learning and optimization algorithms with data from experiments and simulations. We are setting up a line of research on machine-learning models for plasma-enhanced chemical vapor deposition (PE-CVD). It will focus on atomistic simulations with machine-learning potentials and machine learning-assisted accelerated materials development. Goals include analyzing and modulating plasma-enhanced deposition processes for insights into such processes and optimizing experiments based on them.
In this context, we are looking for a motivated and capable post-doctoral researcher to develop machine-learning surrogate models based on computational and experimental data. Candidates should have a Ph.D. degree in physics, chemistry, materials science, computer science, or a related field, as well as demonstrated solid knowledge in computational materials science (ab initio calculations, molecular dynamics simulations), machine learning (kernel models, neural networks, machine-learning potentials), programming skills (Python, C/C++), and an excellent track record of relevant scientific publications.
Your application should include
* motivation letter oriented toward the position and detailing your experience
* scientific curriculum vitae (CV) with contact details
* list of publications (and patents, if applicable)
* contact details of two references
Please indicate if you have an up-to-date scientific profile at a site such as Google scholar, ORCID, or other.
Interested candidates should apply online at https://www.list.lu/en/jobs/ (position M-2012).