Two postdoc positions in atomic-scale computational design of battery materials and interfaces

Monday 13 Jul 20

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The section for Atomic Scale Materials Modelling at DTU Energy, Technical University of Denmark (DTU), is looking for outstanding candidates for two, 2-year postdoc positions within the field of method development for accelerated design and discovery of next-generation sustainable battery materials and interfaces. The research projects are part of the European project BIG-MAP (Battery Interface Genome – Materials Acceleration Platform) under the large-scale, long-term European research initiative Battery 2030+ which seeks to reinvent the way we invent batteries. The BIG-MAP consortium is coordinated by DTU and brings together researchers across the battery discovery value chain from atoms to battery cells, totalling 34 partners from 15 countries and spanning world-leading academic experts, research laboratories and industry leaders.

Project description

The successful candidates will use a combination of electronic structure modelling, machine/deep learning algorithms and automated workflows to bridge different simulational codes and time/length scales in simulations and experiments on battery materials and interfaces. These positions are the first in the BIG-MAP project and will form the basis for the further work on the development of a closed-loop infrastructure for autonomous discovery of battery materials and interfaces. The aim of the projects is to:

  1. Develop machine learning algorithms, which can learn to map multi-scale battery interface dynamics into hierarchically coupled latent spaces that each encode for structures at different length scales. Furthermore, such a model will be integrated with a suitable coupled Markov chain model in the extended latent space to yield a complete dynamics simulator, which can be validated against simulations of battery interface system dynamics at different length and time scales. Uncertainty propagation methods will be integrated within the probabilistic latent space generative models to provide predictive uncertainties that take into account both data and model uncertainties.
  2. Demonstrate a working use case of experiments that drive simulations and simulations that drive experiments, thereby automating and accelerating the discovery process. This will involve several key steps to be performed in collaboration with the BIG-MAP partners, namely: 1) Gathering use-cases where linking of simulation and experiment is viable and identifying the current technological impediments. 2) Helping to establish, implement and put into use an ontology standard that enables interoperability at different scales. 3) Development of automated workflows in AiiDA, SimStack and/or ASE incorporating simulations, experiments and AI-driven methods/tools. 4) Delivering a working demonstrator of a feedback loop between experiments and simulation.

The two projects will be carried out in close collaboration with computational and experimental groups in BIG-MAP and linked to other ongoing projects in the section working on battery materials and machine learning for autonomous materials discovery, e.g. AiMade and SURE.  


Candidates should hold a PhD or equivalent degree in computer science, physics, chemistry or materials science. The candidate must have a strong background in computational chemistry, physics or materials science and/or machine learning, and are expected to have performed original scientific research within the relevant fields listed above for the specific position(s). Moreover, the successful candidate:

  • is innovative and able to work both independently and in cross-disciplinary teams
  • has good communication skills in English, both written and spoken
  • is able to work independently and take responsibility for progress and quality of projects.

The assessment of the applicants will be made by: Head of Section, Professor Tejs Vegge, Assistant Professor Ivano E. Castelli, Researcher Arghya Bhowmik and Dr. Martin Uhrin


We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.


Salary and terms of employment
The appointment will be for 2 years and be based on the collective agreement with the Confederation of Professional Associations. The allowance will be agreed with the relevant union.


The employment is expected to start October 1st, 2020 or shortly thereafter.


Remember to indicate which of the positions you are interested in (not limited to one).

You can read more about career paths at DTU here.
Further information

If you need further information concerning this position, please contact Prof. Tejs Vegge at


Please do not send applications to these e-mail addresses, instead apply online as described below.


We must have your online application by 6 August 2020 (23:59 local time).


Applications must be submitted as one pdf file containing all materials to be given consideration. To apply, please open the link "Apply online," fill in the online application form, and attach all your materials in English in one pdf file. The file must include:

  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • BSc/MSc/PhD diploma
  • List of publications indicating scientific highlights
  • List of References (at least two)

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Energy

The Department of Energy Conversion and Storage is focused on education, research, and development within functional materials and their application in sustainable energy technologies. The Department is focusing on functional materials and their application in sustainable energy technology. Our research areas include fuel cells, electrolysis, polymer solar cells, magnetic refrigeration, superconductivity, thermo electrics, sustainable synthetic fuels, and batteries. Additional information about the department can be found on


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