PhD The use of machine learning and advanced modelling

Afdeling

Faculty of Science and Engineering

Organisatie

Rijksuniversiteit Groningen, University of Groningen, V25.0124

Functiebeschrijving

To enable the development of new, superior perovskite materials and solar cells, the successful candidate will use and develop machine learning techniques and advanced numerical simulation modelling to quantitatively study the electrical characteristics of state-of-the-art perovskite solar cells.

The efficiency and stability of perovskite solar cells are highly dependent on the processing of the materials. Hence, process optimization is needed in order to get the best performance. There are two sides to this type of work: on the one hand optimization leads to better devices, but it is also a massive opportunity to learn from large datasets.

Process optimization is a fiendishly complex problem, however. The efficiency, reproducibility, and stability/lifetime of perovskite solar cells strongly depends on many—largely unknown—parameters. This is a problem in any research lab, but even more so at the industrial scale. This project will tackle exactly this problem by providing deep links and insights between processing conditions and inline data on the one hand, and performance on the other hand. For example, how do processing conditions translate into perovskite formation, physical properties, and solar cell performance? Which processing parameters are key? Are the parameters that yield the highest efficiency also the ones that lead to the best stability?

Ultimately, the PhD candidate will develop a neural network to identify specific properties/processing conditions/device layouts that are key determinants for efficiency and stability. The industrial partners will supply inline date (PL, XRD of film formation). Importantly, we will gain understanding of the underlying physics. At every step, we will compare the modelling with experimental data to ensure the modelling is correct. In our previous work and other projects, we routinely achieve agreement with the experimental data that is well within the experimental error.

Within this PhD project, we will use the suite of machine learning tools that is readily available in Python packages. In other words, we will not focus on the development of new machine learning tools as everything we need is already available. Instead, we use the existing tools for discovering trends in experimental data, ideally, based on explainable models. The major benefit of explainable models manifests itself in the second step: generating physical insight that is more widely applicable.

In order to connect the machine learning models to the underlying physics, we will use a combination of device-scale drift-diffusion modelling and atomic scale molecular dynamics and quantum chemical modelling. In doing so, we cover both ends of the lengthscales that are relevant to perovskite solar cells: Effects that cannot be captured by drift-diffusion will be treated at the atomistic scale and vice-versa.

A deep understanding of device physics, numerical modelling, and computer programming are, therefore, required. The PhD student will be operating at the Zernike Institute for Advanced Materials, one of the leading institutes in the field of materials science, and will be supervised by Prof. Dr Jan Anton Koster, an expert in the field of photovoltaics.

Organisation
The University of Groningen is a research university with a global outlook, deeply rooted in Groningen, City of Talent. Quality has been our top priority for over four hundred years, and with success: the University is currently in or around the top 100 on several influential ranking lists.

The Faculty of Science and Engineering (FSE) is the largest faculty within the University. We offer first-rate education and research in a wide range of science and engineering disciplines, from classical disciplines such as mathematics, astronomy and mechanical engineering, to interdisciplinary fields such as artificial intelligence, pharmacy and nanoscience. Our community has an open and informal character with students and staff from around the world.

The position we offer will be embedded in the Zernike Institute for Advanced Materials. The research group Photophysics and OptoElectronics is part of the Zernike Institute for Advanced Materials in the Faculty of Mathematics and Natural Sciences of the University of Groningen. The group's main research interests lie in the use of novel semiconducting materials for optoelectronic applications and devices. The group provides a lively, internationally oriented scientific environment with excellent facilities.

Functie-eisen

- University MSc degree in Physics, Material Science, or related disciplines.
- The applicant cannot hold a PhD degree.
- Fluency in spoken and written English.

You are expected to

- Hold a (research) master degree (or will graduate before appointment date) in physics or a similar, related field.
- Have demonstrable experience in numerical modelling.
- Have demonstrable experience in computer programming.
- Show ability to collaborate in an interdisciplinary environment.
- Have strong communication skills and are motivated to disseminate results to both scientific peers and a broad audience.
- Be proficient in the English language (oral and written) e.g. with a minimum IELTS score of 7.0 overall and 6.5 on parts.
- Be strongly motivated to obtain a PhD degree.
- Technical skills: An MSc degree in physics, material science or engineering (or equivalent) is required. A demonstrable background in computer programming and numerical simulation is essential.

Arbeidsvoorwaarden

Contractduur: 48 months.

We offer you in accordance with the Collective Labour Agreement for Dutch Universities

- A salary of € 2.901 gross per month in the first year, up to a maximum of € 3,707 gross per month in the fourth and final year for a full-time working week.
- A holiday allowance of 8% and an 8.3% year-end bonus.
- A full-time position (1.0 FTE) for four years; first, you will get a temporary position of twelve months with the option of renewal for another thirty six months; prolongation of the contract is contingent on sufficient progress to indicate that successful completion of the PhD thesis within the contract period is to be expected. A PhD training programme is part of the agreement and you will be enrolled in the Graduate School of the Faculty of Science and Engineering.

The conditions of employment are available at the University of Groningen website under Human Resources: https://www.rug.nl/about-us/work-with-us/

Sollicitatie

Do you want to become a member of our team? Please send your application to us, by submitting the following documents: 1. Letter of application (Please name the document as: Personal letter, Family name, Ref. number). 1-3 pages where you: - Introduce yourself. - Describe your previous experience of relevance for the position (e.g. education, thesis work and, if applicable, any other research activities). - Describe your future goals and future research focus. - Copies of bachelor and/or master’s thesis. - Attested copies and transcripts of completed education, grades and other certificates, eg. TOEFL test results. 2. Curriculum vitae (Please name the document: CV, Family name, Ref. number) 3. Copy of the latest degree/qualification 4. Two letters of recommendation. You may apply for this position until 31 March 11:59pm / before 1 April 2025 Dutch local time (CET) by means of the application form (click on "Apply" below on the advertisement on the university website). Please note that the data that you provide will be used exclusively for the purpose of professional profiles’ evaluation and selection, and in order to meet the requirements of the University of Groningen. Your data will be processed by the University of Groningen, based in Groningen, Broerstraat 5, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security. We are an equal opportunity employer and value diversity at our University. We are committed to building a diverse faculty so you are encouraged to apply. Our selection procedure follows the guidelines of the Recruitment code (NVP), http://nvp-plaza.nl/download/?id=7714 and European Commission's European Code of Conduct for recruitment of researchers, https://euraxess.ec.europa.eu/jobs/charter/code Unsolicited marketing is not appreciated.

Meer informatie

Voor meer informatie over deze vacature kunt u contact opnemen met:

Prof. L.J.A. Koster
[email protected]

Noemt u in uw sollicitatie altijd het vacaturenummer V25.0124

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