Postdoc (f/m/d) in the area of machine learning for materials science and chemistry

  • Stellenausschreibung:
  • Stellenart:

    Postdoc, Academic Employee

  • Stellennummer:


  • Fakultät/Abteilung:

    Department of Computer Science

  • Institut:

    Institute of Nanotechnology (INT)

  • Eintrittstermin:

    December 2021

  • Bewerbungsfrist:

    October 15th, 2021

  • Kontaktperson:

  • Job description

    Your responsibilities involve the initialization of collaborations within the German-Canadian Materials Acceleration Center (GC-MAC) project. This includes independent planning and implementation of research projects in the area of artificial intelligence and machine learning applied to materials science, especially for energy materials. Research areas relevant to the project are regression models (e.g. graph neural networks) for materials property prediction, generative models for inverse material design, machine learning based material simulations, probabilistic models for autonomous experiments and similar areas. The application includes among others materials for hydrogen and CO2 electrocatalysis, membrane materials as well as battery materials. In addition to your scientific tasks, you will be actively involved in the GC-MAC project. This includes planning and implementatin as well as participation in (international) project meetings, tutorials and workshops.


    Personal qualification

    You have a university degree in the field of materials science, physics, chemistry or computer science with a completed PhD and experience in the field of (energy) materials, materials simulations and machine learning methods, which you can demonstrate through relevant publications. Independent and creative work, strong collaboration and communication skills and a strong interest in interdisciplinary work are desired.



    Salary category 13, depending on the fulfillment of professional and personal requirements.



    For further information please contact Prof. Friederich, E-Mail:


    More information


    We prefer to balance the number of employees (f/m/d). Therefore we kindly ask female applicants to apply for this job. Recognized severely disabled persons will be preferred if they are equally qualified.