ERC-funded postdoc position: Machine Learning for Angstrom-Scale Technology (not available anymore)
Interested in turning organic molecules into the building blocks for tomorrow’s nm-scale devices and machines? For its research towards mechanical engineering on the molecular scale (molecular electronics & machines), the department Functional Nanostructures at Surfaces (PGI-3) offers a postdoc position in the field of
DescriptionIn the framework of the ERC-funded 5 year project “Controlled Mechanical Manipulation of Molecules (CM3)” a postdoc position in the field of machine learning is available at the Peter Grünberg Institute (PGI-3) of Forschungszentrum Jülich Research Center, Germany. The project goal is full conformational control over individual molecules during manipulation with a scanning probe microscope at cryogenic temperature. The molecules will be brought into otherwise inaccessible metastable conformations to study fundamental effects, and used to construct, e.g., a molecular scale electrical motor.
The applicant will use machine learning techniques to analyze and structure the experimental data (forces acting during manipulation) on-line during the experiment and also a posteriori. This includes applying classical machine learning methods to classification and regression problems and to signal processing (e.g., logistic regression, kernel regression, wavelet analysis). Further details about the research project are available from Dr. Christian Wagner (c.wagner [at] fz-juelich.de).
InstitutionThe project is funded by a starting grant of the European Research Council (ERC) for the project “Controlled Mechanical Manipulation of Molecules CM3”, and carried out by the Forschungszentrum Jülich (FZJ). The FZJ is one of the largest German research centers. It offers excellent opportunities for research in an international environment. Within the Jülich-Aachen Research Alliance (JARA), founded under the auspices of the German Excellence Initiative, it is closely linked to the RWTH Aachen University. Salaries are competitive (TvöD + allowance depending on the candidate's profile), and there is no teaching load. Equal opportunities are a cornerstone of our staff policy for which we have received the "TOTAL E-QUALITY" award.
RequirementsThe applicant needs solid experience in the development and application of machine learning techniques and should be able to work independently in the interdisciplinary environment of a nanotechnology lab.
ApplicationFor further information about the project contact Dr. Christian Wagner (c.wagner [at] fz-juelich.de). Please send your application, including the relevant documents and stating your interests, preferably via e-mail (c.wagner [at] fz-juelich.de).
Peter Grünberg Institut (PGI-3)
▶September 6th, 2018We are happy that MSc Michael Maiworm joins us till January to work on molecular control algorithms.
▶August 16th, 2018Paper on fast SQDM controller online Read at IEEE..
▶August 1st, 2018We welcome our new group member MSc Rustem Bolat.
▶June 27th, 2018Single molecule finally stands on its own two feet! Read at Nature..
▶June 1st, 2018We welcome our new group members Dr. Hadi Arefi and MSc Marvin Knol. Scientists..
▶May 18th, 2018New article on the physics of molecular quantum dots online now. Get pdf.. View at PRL..
▶September 5th, 2017ERC starting grant for controlled molecular manipulation. more..