PhD or Postdoc in "Machine Learning for Materials"

Advisers: Dr. Matthias Rupp and Prof. Dr. Matthias Scheffler
Location: Fritz Haber Institute of the Max Planck Society, Berlin, Germany
Topic: Kernel-based machine learning models for materials science
Keywords: Electronic structure, machine learning, method development

We are looking for a new colleague to join the research group "Machine Learning for Materials" at the Theory Department of the Fritz Haber Institute of the Max Planck Society in Berlin as PhD student or postdoctoral researcher. You will be working with Matthias Rupp, the leader of the group, and Matthias Scheffler, the departments director.

This is an opportunity to be on the forefront of development for models that combine first principles materials science with machine learning. This research direction is rapidly gaining interest and momentum, and offers the opportunities of a young field. Work will be part of the Novel Materials Discovery (NoMaD) project. Based on this, you will be involved in the design, development and application of state-of-the-art machine learning models for properties and functions of materials.

Ideal candidates will have a background in physics and computer science, in particular solid knowledge in condensed matter physics and kernel-based machine learning, an excellent track record of relevant scientific publications, and sound programming skills in C, C++ or Fortran, as well as Python or Mathematica.

Further information:

* Theory Department, Fritz Haber Institute of the Max Planck Society
* NoMaD Laboratory, a European Center of Excellence

Example publications:

* Rupp et al, Phys Rev Lett 108: 058301, 2012. DOI 10.1103/PhysRevLett.108.058301
* Rupp et al, J Phys Chem Lett 6(16): 3309, 2015. DOI 10.1021/acs.jpclett.5b01456
* Ghiringhelli et al, Phys Rev Lett 114: 105503, 2015. DOI 10.1103/PhysRevLett.114.105503

Applications should include information on

* why you apply for this position, your interests and potential contributions
* programming skills and experience in method development
* Postdoc: complete list of publications and three faculty acting as reference
* PhD student: transcript of courses and exams with grades and two faculty acting as reference

If you have an up-to-date scientific profile at a site such as Google scholar, ResearchGate, ORCID, or other, please indicate. Postdoc candidates who pass initial screening will be expected to write a research proposal as part of the admission process. Applications will be evaluated on an ongoing basis until a suitable candidate is found.

Interested candidates should contact Matthias Rupp directly (matthias.rupp at fhi-berlin.mpg.de).