Doctoral Candidate in AI-Guided CO2 Conversion

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 Department of Applied Physics is now looking for a

Doctoral Candidate in AI-Guided CO2 Conversion

The Computational Electronic Structure Theory (CEST) group at Aalto University is hiring a doctoral candidate. In this position, you will work in a collaborative team from Aalto University’s Schools of Engineering and Science. You will have a chance to make an impact on the green and digital transition by applying tools from artificial intelligence (AI) to CO2 conversion. Our objective is to optimize the conversion of captured CO2 (from e.g., waste combustion, flue gases or the atmosphere) into useful products, thereby closing the carbon cycle and eliminating fossil-based raw materials.  

Your role and goals

You will be developing data science and machine learning approaches and apply them to optimize and better understand catalyst materials and catalytic conversion processes. You will also be developing digitalization workflows for the experimental data generated in the project.  The position is part of an Academy of Finland funded research consortium. You will collaborate closely with the team members and integrate computational, literature and experimental data into a materials discovery and optimization workflow.

Your experience and ambitions

We welcome candidates with a Master’s degree in (computational) physics, chemistry or materials science who are curious about applied machine learning in the natural sciences. Prior machine learning or Python experience is a strong bonus, but not a must. We seek colleagues who enjoy coding, scripting and analytics, and are keen to push the boundaries of data-driven materials science and materials exploration. This project requires creative thinking and programming, as well as technical expertise in materials simulations and a broad understanding of surface science and catalysis. We further appreciate willingness to travel, teach and mentor, collaborate and communicate science.

What we offer

In the Computational Electronic Structure Theory (CEST) group, led by Prof. Patrick Rinke, we advance electronic structure theory and machine learning to pursue innovative applications towards future technologies. We are a multi-cultural and cross-disciplinary team, with complementary subgroups and talents. Our group is part of the Finnish Center for Artificial Intelligence (https://fcai.fi/ ) and you will be embedded in a lively community at the crossroads of AI, chemistry, physics and materials science. You will train in machine learning applications with experienced developers, meet our global network of collaborators, join us at scientific meetings, help us organize research workshops and get involved in academic and diversity outreach. In combination with the academic development courses at Aalto University, we will help you grow a competitive and international career profile.

The fixed term contract is initially for two years then extended to another two years after a successful mid-term progress review. The total duration of Ph.D. studies is four years. The annual workload of research and teaching staff at Aalto University is currently 1612 hours. Aalto University follows the salary system of Finnish universities. The starting salary for a Doctoral candidate is approx. 2560€/month and it increases as you progress in your research and studies. The contract includes Aalto University occupational healthcare. The primary workplace will be the Otaniemi Campus at Aalto University.

Ready to apply?

To apply for the position, please submit your application including the attachments mentioned below as one single PDF document in English through the link ’Apply now’ link at the bottom of the web page. 

(1)   Letter of motivation
(2)   CV including list of publications
(3)   Degree certificates and academic transcripts
(4)   Contact details of at least two referees (or letters of recommendation, if already available) 

The deadline for applications is February 25, 2022. The position will be filled as soon as a suitable candidate is identified. For additional information, kindly contact Prof. Patrick Rinke. Aalto University reserves the right for justified reasons to leave the position open, to extend the application period, reopen the application process, and to consider candidates who have not submitted applications during the application period.

Please note: Aalto University’s employees and visitors should apply for the position via our internal system Workday -> find jobs (not external aalto.fi webpage on open positions) by using their existing Workday user account

About Finland

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 and was just listed again as the happiest country in the world: https://worldhappiness.report/news/its-a-three-peat-finland-keeps-top-spot-as-happiest-country-in-world/ . For more information about living in Finland: https://www.aalto.fi/services/about-finland

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