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Postdoc Position in Development of Computational Techniques for Battery Materials

Technical University of Denmark

Location: Lyngby - Denmark
Salary: Not Specified
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 12th March 2019
Closes: 5th April 2019

DTU Energy at the Technical University of Denmark, DTU, invites applications for a 2-year postdoc position in the area of computational methods for battery materials. The project, which is aligned with the Department’s focus area on battery materials and technologies, is funded by the Villum foundation and the European Union through the H2020 FET Open project Salbage. 

The Salbage project aims at developing a new Sulfur-Aluminium Battery with an Advanced Polymeric Gel Electrolyte, which would represent a revolutionary breakthrough in the energy storage market due to the utilization of highly available raw materials for the anode and the cathode in combination with a safe electrolyte. 

The postdoc position involves collaboration with international academic partners, e.g. the groups of Prof. Yang Shao-Horn at Massachusetts Institute of Technology, Prof. Ángel Rubio at the Max Planck Institute for the Structure and Dynamics of Matter in Hamburg. 

Project description

We have recently implemented several computational tools

  • Constrained-density functional theory (c-DFT) combined with a Marcus theory framework in the GPAW code with the aim of studying charge transfer processes in battery cathode materials, electrolytes and cathode-electrolyte interfaces.
  • The Cluster-expansion code CLEASE integrated in the Atomic Simulation Environment (ASE) to study the disorder in cathode material upon charge and discharge.
  • An algorithm to speed up the Nudged Elastic Band (NEB) method by using symmetry considerations.

The successful candidate will work on the further development and testing of these techniques and on the implementation of new ones, such us

  • A new scheme to calculate the total energy of charged supercells.
  • A Kinetic Monte Carlo framework to couple to the Cluster Expansion implementation.
  • Frozen Embedding Density (FDE) in the GPAW code in order to speed up molecular dynamic simulations.
  • Machine Learning algorithms to predict open circuit voltages and ion diffusivities in battery materials.

These tasks will be prioritize according to the background and skills of the selected candidate.

The project will be carried out in close collaboration with experimental groups. The project will be also linked to other computational projects working on screening of materials for lithium-ion and aluminium-sulfur batteries.


Candidates should have a PhD degree in computational/theoretical physics, chemistry or materials science. 

The successful candidate:

  • Has good communication skills in English, both written and spoken
  • Is able to work independently and take responsibility for progress and quality of projects
  • Enthusiasm for working in collaboration with experimental groups
  • Well established skills to work in a team
  • Strong computer programming skills


The assessment of the applicants will be made by: Associate Professor Juan Maria García Lastra and Head of Section, Professor Tejs Vegge 

Salary and appointment terms

The appointment will be based on the collective agreement with the Confederation of Professional Associations. The allowance will be agreed with the relevant union. 

The position is for two years. 

The employment is expected to start June 1st 2019 or soon thereafter. 

Further information

If you need further information concerning this position, please contact Associate Prof.  Juan Maria García Lastra at 

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


We must have your online application by 5 April 2019.  

To view the full announcement and to apply:   

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* Salary has been converted at the prevailing rate on the date placed
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