Are you looking for a 3-year postdoc position in density functional theory simulation and applied deep learning for battery materials discovery? The research position is a part of the project “Autonomous agents of Discovery for earth-Abundant Na-ion battery cathodes (ADANA)” that is led by Assoc. Prof. Arghya Bhowmik at DTU from computational side and co-led by Prof. Dorthe Ravnsbæk at Arhus University from experimental side. ADANA intends to pioneer a multi-objective generative inverse design for disordered solid-state battery materials with the right properties by exploring a practically infinite chemical-structural phase space. We will develop and deploy deep learning based descriptor discovery to make the design space accessible to human understanding.

Responsibilities and qualifications: 
You will 

(a) train and deploy equivariant graph neural network models as surrogate simulators for Na-ion battery materials using local and European GPU HPCs at an unprecedented scale for screening across broad chemical space 

(b) develop and utilize in-house 3D graph representation based reinforcement learning methods for solving disordered crystal structures 

(c) develop, train and deploy periodic graph generative models for property conditioned inverse design of disordered, defective battery materials.

(d) use state of the art explainable AI methods for deducing materials design rules from deep learning models. 

Necessary software engineering will be done for scalability and distributed trainability. This will allow us to generate petabytes of data over entire phase spaces of materials, allowing data-driven breakthrough science.

The project will be carried out in close collaboration with external partner groups that are considered the world’s leading materials simulation and deep learning method development groups including  Prof. Klaus Robert Muller (TU Berlin), where you will have exchange visits. The activities are linked to other ongoing projects in the Section working on clean energy materials and machine learning for accelerated materials discovery. 

As a formal qualification, you must hold a PhD degree (or equivalent). Candidates should hold a PhD or equivalent degree in physics, chemistry or materials science. The candidates must have a strong background in atomic scale simulations, have good programming skills; are interested in developing machine learning methods; and are expected to have performed original scientific research within the relevant fields listed above for the specific position. Demonstrated ability to work in collaborative research environments and a proven track record of high-quality research and publications in relevant areas are also required.

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

The period of employment is 3 years starting from 1 January 2025 or as soon as possible thereafter.

You can read more about career paths at DTU here.

Further information 
Further information may be obtained from Assoc. Prof. Arghya Bhowmik at arbh@dtu.dk.

You can read more about DTU Energy at www.energy.dtu.dk 

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

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark.

Application procedure 
Your complete online application must be submitted no later than 15 October 2024 (23:59 Danish time). 

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

• Application (cover letter)
  • Please state if: you have experience with machine learning model development for atomic scale simulation 
• CV
• Academic Diplomas (MSc/PhD – in English)
• List of publications 

Applications received after the deadline will not be considered.

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

DTU Energy
The Department of Energy Conversion and Storage (DTU Energy) focuses on research and development of functional materials, components, and systems for sustainable energy technologies. The technologies include fuel cells, electrolysis, power-to-x, batteries, and carbon capture. The research is based on strong competences on electrochemistry, atomic scale and multi-physics modelling, autonomous materials discovery, materials processing, and structural analyses. We also focus on educating engineering students at all levels, ranging from BSc, MSc, PhD to lifelong learning students. We have about 270 dedicated employees. Read more about us at www.energy.dtu.dk 

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DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.