Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto has six schools with nearly 11 000 students and a staff of more than 4000, of which 400 are professors. Our main campus is located in Espoo, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness in the future as well. This is why we warmly encourage qualified candidates from all backgrounds to join our community.
The School of Chemical Engineering is one of the six schools of Aalto University. It combines natural sciences and engineering in a unique way.
The Department of Chemistry and Materials Science is looking for motivated
Doctoral Candidate to join the Computational Chemistry group
In this position, you will have a chance to be a part of research project that is focused on developing explainable artificial intelligence (XAI) based tools to accelerate the development of redox flow battery (RFB) chemistries.
Specifically, we will develop DFT based computational screening and machine learning (ML) tools to facilitate rapid evaluation of RFB materials to identify the most promising candidates. We will use new Explainable Artificial Intelligence (XAI) methods to rationalize the vast amount of computational data. With DFT methods we can compute the structures and properties of tens of thousands of molecules, and XAI will then enable us to pinpoint the important molecular features contributing to the redox potential and other properties such as stability and reactivity. Armed with this information, we can design selected sets of new promising molecules and evaluate their properties more rigorously with computational methods. The computational group will work in close collaboration with flow battery group in University of Turku (Prof. Peljo) and organic chemistry group in University of Jyväskylä (prof. Pihko).
Your tasks will include the DFT modelling of various organic and metal-organic molecules. The DFT modelling will provide descriptors for the ML methods. You will also participate in the ML modelling of the redox potential, stability and reactivity. You will learn how to develop very advanced DFT-XAI tools to solve real world materials development problems. In this position you will also have opportunity to learn to interact with experimental groups trying to solve the same problems as you do.
You will join the skilled computational chemistry group
lead by prof. Kari Laasonen.
Your background and expertise
You have a Master’s degree (or equivalent) in a relevant field like chemistry, physics or materials science. We expect you to have a good knowledge of quantum chemical modelling, preferably the DFT methods. The knowledge of machine learning methods is a bonus.
If you are chosen for this position, you will apply the study right for doctoral studies in Aalto University School of Chemical Engineering. Thus, please check the student information and admission criteria https://www.aalto.fi/en/study-options/aalto-doctoral-programme-in-chemical-engineering
. In particular, please pay attention to mandatory skill level in English.
What we offer
We offer you an inspiring scientific environment with three modelling groups and excellent computational facilities including access to one of the largest supercomputers in the world.
The expected starting salary for a doctoral candidate is approximately 2500€/month and salary will increase with responsibilities and performance over time. The contract includes occupational health care and Finland has a comprehensive social security system. Aalto University provides excellent learning and development opportunities, commuter ticket benefit and Unisport offers versatile exercise services with staff discount.
The project has funding for the doctoral candidate altogether for four years. The position can be filled immediately.
Ready to apply?
If you want to join our community, please submit your application through our online recruitment system by using the link on Aalto University’s web page ("Apply”).
Please include the following documents in English.
Motivation letter: free form letter where you describe yourself and why you are interested in this particular position.
CV describing education and employment history
Course transcripts of your B.Sc. and M.Sc. degrees with grades
The call is open until February 15, 2022, but we will start reviewing and interviewing candidates immediately. The possible interviews will be organized using video meetings.
If you have any questions, professor Laasonen is happy to give you more information about the position email@example.com
Aalto University’s employees and visitors please note: you should apply for the position via our internal system Workday -> Career -> find jobs (not external aalto.fi webpage on open positions) by using your existing Workday user account.
Finland is a great place for living with or without family - it is a safe, politically stable and well-organized Nordic society. Finland is consistently ranked high in quality of life. For more information about living in Finland: https://www.aalto.fi/services/about-finland
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