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PhD project on molecular-scale engineering

Advertising institute: PGI-3 - Functional Nanostructures at Surfaces
Reference number: D058/2018, Physics, Chemistry

In this high-profile, ERC-funded research project we work on the realization of molecular-scale machines and devices. To achieve this ambitious goal we combine low-temperature UHV scanning probe microscopy, with dedicated simulation and machine learning techniques. Working together in a group with experts from experimental and theoretical physics, as well as computer science, the PhD project plays a key role for the development of controlled mechanical manipulation of molecules.

Exemplary tasks
Integration of machine learning techniques and control algorithms (e.g. reinforcement learning, SVM) into the SPM experiment
Construction of supramolecular structures by SPM
Visualization of measured data using immersive 3D glasses (Oculus rift)
Controlled charge transport spectroscopy of molecular building blocks

Our offer:
Cutting-edge research, fast PhD: 3.5 years max, excellent instruments and equipment, training in fields like machine learning and control theory, very low teaching load, 66% TvöD 13 salary

Your profile:
For this position, we are looking for a highly-motivated student with a master in physics, chemistry, engineering or a related discipline (grade 2.0 or better). Experience with UHV systems and/or scanning probe microscopy as well as programming skills are advantageous.

Read more:

Forschungszentrum Jülich aims to employ more women in this area and therefore particularly welcomes applications from women. We also welcome applications from disabled persons.

For further information about the project contact Dr. Christian Wagner (

Please send your application, including the relevant documents and stating your interests, preferably via e-mail to
Christian Wagner
Peter Grünberg Institut (PGI-3)
Forschungszentrum Jülich
52425 Jülich

Deadline for applications: 01.04.2018

This job offer as pdf file:  PhD project on molecular-scale engineerings (PDF, 368 kB)