Applications are invited for a PhD fellowship/scholarship at Graduate School of Natural Sciences, Aarhus University, Denmark, within the Physics and Astronomy programme. The position is available from February 2022 or later.
Title:
Understanding the Reactivity of Catalytic Materials with Machine Learning
Research area and project description:
Materials with a catalytic function may be found in such diverse places as chemical reactors or as dust grains in molecular clouds in the interstellar space. Despite their crucial role in society and the Universe for accelerating chemical reactions, the reliable description of catalytic properties and the prediction of what materials may be even better catalysts than those we know already is still challenging. As catalysts are typically rather complex and may consist of different types of (nanostructured) materials, experiments alone are often insufficient to understand the factors controlling their reactivity or to identify the “active sites” responsible for the actual catalytic effect. Predictive-quality theory and computer simulations may provide crucial input, e.g. in the form of adsorption energies of key atoms or molecules at different types of active site motifs of the material. While it is possible to use quantum mechanical calculations (density functional theory, DFT) to study simple reactions and simple model catalysts such as high-index facets of metals or oxides, the computational demands of such an approach can quickly become prohibitively large for realistic materials, i.e. interstellar dust grains in the Universe or the catalytic materials that are actually present inside chemical reactors.
In this project, the successful PhD candidate will develop and apply machine learning (ML) techniques to help tackle these challenges. ML can both help us speed up the prediction of key catalytic parameters such as adsorption energies compared to DFT and allow us to gain physical insights into the key factors controlling catalytic reactivity through interpretation of the patterns in the data that the ML model has learned [1-2]. The PhD candidate will benefit from an inspiring international environment and collaborations with theoretical and/or experimental partners.
For more background of this PhD project, please visit:
https://phys.au.dk/research/research-areas/catalytic-structure-activity-relationships-with-machine-learning/
References:
- M. Andersen, S. Levchenko, M. Scheffler, K. Reuter. Beyond scaling relations for the description of catalytic materials. ACS Catal. 9, 2752 (2019)
- M. Andersen, K. Reuter. Adsorption enthalpies for catalysis modeling through machine-learned descriptors. Acc. Chem. Res. 54, 2741 (2021)
Qualifications and specific competences:
Applicants to the PhD position must have a Master’s degree in Physics, Chemistry, Nanoscience or related. If applying for a 4+4 PhD position, the applicant must have a bachelor’s of science degree and be one year into the Master’s program.
Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Department of Physics and Astronomy, Aarhus University, Ny Munkegade 120, DK-8000 Aarhus C., Denmark.
Contacts:
Applicants seeking further information for this project are invited to contact:
Associate Professor Mie Andersen, mie@phys.au.dk
Application procedures
Before you apply, please read the application guide thoroughly. You can find the guide here.
How to apply:
1) Find the application form:
Go to https://phd.nat.au.dk/for-applicants/apply-here/ – Note, the online application system opens on 1 September 2021.
Choose November 2021 Call with deadline 1 November 2021 at noon (11.59 AM CET).
You will be directed to the call, and must choose the programme “Physics and Astronomy”.
2) Fill in the following information:
- Personal information
- Academic background
- Admission
- Financing (if any)
- Study: In the dropdown menu you must choose the project: “Understanding the Reactivity of Catalytic Materials with Machine Learning (URCMML)”
- Source (how you found out about the call)
Next to some of the information fields you will find a number. Click on the number to get further directions on how to fill in the information field/what information is needed.
3) Application attachments:
Please be aware that you cannot submit the application if one or several of these documents have not been uploaded.
If you wish to upload more than one document under each section, you must scan/merge all documents into one large PDF file and upload this. Please note that we reserve the right to remove scientific papers, large reports, theses and the like. Instead you can indicate a URL where the information is available.
All information in the application must be in English or Danish, preferably English. A certified English translation is required for documents written in languages other than English or one of the Scandinavian languages (i.e. Norwegian, Swedish or Danish) languages.
As a minimum, all applications must include (pdf-files only, max. 20 MB, and no zip):
One reference (template for references)
- Curriculum vitae,
- Motivation (max. 1 page)
- Transcripts, grade point averages (weighted and unweighted), and diploma(s) for both Bachelor’s and Master’s degree. If the original documents are not in English or one of the Scandinavian languages (i.e. Norwegian, Swedish or Danish) then copies of the original documents as well as a certified English translation must be attached.
- Project description (½-4 pages). For technical reasons, you must upload a project description. When – as here – you apply for a specific project, please simply copy the project description above, and upload it as a PDF in the application. If you wish to, you can indicate an URL where further information can be found. Please note that we reserve the right to remove scientific papers, large reports, theses and the like.
- Documentation of language skills if required.
After submission of the application, you will receive a confirmation e-mail with an application ID, you should use for reference if needed.
The graduate school reserves the right to verify the authenticity of your educational diploma and transcripts:
- Request additional information to verify an application.
- Reject the application if it is proven, or if the University has reasonable belief, that the information provided is false or if the applicant refuses to provide the requested information, whether or not an offer has already been made.
- For further information on applying, assessment procedures, etc. please see the GSNS Application Guide.
Please note:
- The programme committee may request further information or invite the applicant to attend an interview.
- The project will only be initiated if final funding (from the graduate school/the faculty) is secured.
All interested candidates are encouraged to apply, regardless of their personal background.
Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants.