Postdoctoral position in electronic, multiscale and machine-learning methods for battery-relevant...

Updated: almost 3 years ago
Job Type: FullTime
Deadline: 16 Aug 2021

The Battery Interface Genome – Materials Acceleration Platform (BIG-MAP) project (http://www.big-map.eu u) is a consortium of 34 academic and industrial partner groups funded by the European Commission. The announced position is part of BIG-MAP and will be placed at the Department of Chemistry at the Ångström Laboratory of Uppsala University. The host group (http://www.teoroo.kemi.uu.se/ )  collaborates with the Karlsruher Institut für Technologie  (KIT) and École polytechnique Fédérale de Lausanne (EPFL) on multiscale modelling workflows and interoperability and the with University of Cambridge and the University of Vienna on the development of machine-learning potentials and property prediction of battery materials and molecules.

The host group is strongly involved in research on –combinations of– electronic structure methods (DFT, ab initio and semi-empirical), atomistic advanced (reactive) force fields and kinetic modelling. A range of applications involving interface chemistry, redox properties, energy materials and intermolecular interactions are being explored. 

Work duties: The main duties involved in a postdoctoral position is to conduct research. Teaching may also be included, but up to no more than 20% of working hours. The main focus of the current research project is the exploration and assessment of interaction models and data interoperability at different levels and the development of modelling workflows and strategic simulations, all in the area of energy materials and interfaces consistent with the goals of the BIG-MAP project.

Requirements: For employment as postdoc, the applicant should have a PhD exam or an international equivalent within the field of Chemistry, Physics, Materials Science or other for the position relevant fields, within a maximum of three (3) years before the final application date. Under certain circumstances, an earlier PhD can be acceptable. Certain circumstances include leave due to illness, parental leave, work in trade unions, etc. The assessment of applications is based primarily on the applicant's ability to conduct independent research based on scientific skill. Greater importance will be attached to the quality of individual scientific work than to the number of publications.

The applicant is expected to (i) have a solid background in quantum chemistry modelling of materials and molecules, (ii) possess at least moderate skills in the application of machine learning to scientific problems, (iii) possess good working skills in programming/ scripting, data handling and interoperability, and (iv) have some experience with atomistic (force-field) models, MD simulations and multi-scale modelling. Finally, (v) the applicant is expected to have a very good knowledge of written and spoken English and (vi) possess good collaborative skills, drive and independence.

Additional requirements: Consideration will also be given to how the applicant’s experience and skills complement and strengthen the BIG-MAP team as well as the ongoing research within the research group.

Salary: Individual pay.

Starting date: 2021-09-15 or as otherwise agreed.

Type of employment: Temporary position for two years.

Scope of employment: 100 %

For further information about the position please contact: Professor Kersti Hermansson, (+46-18-4713767, [email protected] ).

Please submit your application by 16 August 2021, UFV-PA 2021/2836.

Are you considering moving to Sweden to work at Uppsala University? If so, you will find a lot of information about working and living in Sweden at www.uu.se/joinus . You are also welcome to contact International Faculty and Staff Services at [email protected] .



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