PhD student position in Designing the free energy landscap

We are looking for a PhD student to join our research team for a project focused on designing the free energy landscape of photoactive molecular materials, in particular for molecular solar thermal storage (MOST) materials.

Project description
Photoactive molecules play key roles in several potential solar energy applications, e.g., in MOST systems or for improving the efficiency of solar cells. These technologies can make crucial contributions to a sustainable energy economy enabling decentralized energy harvesting, storage, and delivery based entirely on earth-abundant raw materials. To be viable from an application standpoint, the underlying materials must, however, still be improved in various aspects.

In practice, the molecular materials used in the aforementioned cases require careful design through addition of side groups. The rotational and orientational degrees of freedom introduced in this fashion create a complex free energy landscape and a high-dimensional parameter space for molecular design. This motivates to the key scientific questions and goals at the center of this project.

In this project you will combine accurate quantum mechanical calculations with machine learning techniques and methods for sampling free energy landscapes. To this end, you will be able to draw from three areas of expertise in our group, pertaining respectively to MOST systems, materials dynamics, and model building. Crucially, the computational results will also directly impact experimental research via several well established experimental collaborations.

This recruitment is connected to the Wallenberg Initiative Materials Science for Sustainability (WISE). WISE, funded by the Knut and Alice Wallenberg Foundation, is the largest-ever investment in materials science in Sweden and will encompass major efforts at Sweden’s foremost universities over the course of 10 years. The vision is a sustainable future through materials science.

All early-stage researchers recruited into the WISE program will be a part of the WISE Graduate School, an ambitious nationwide program of seminars, courses, research visits, and other activities to promote a strong multi-disciplinary and international network between PhD students, postdocs, researchers, and industry.

Major responsibilities
During this project you will construct and apply atomic scale models using machine learning techniques to predict thermodynamic, kinetic, and optical properties of molecular materials. As part of the project, you will be expected to communicate research results both orally at international conferences and in writing in scientific journals. You will be able to employ and contribute to the continued development of our in-house codes

Qualifications
You should hold a master's level degree in chemistry, physics, materials science or an equivalent degree, with a sound background and interest in one or more of the following fields computational physics, organic chemistry, condensed matter physics, materials physics, and machine learning.

Experience in electronic structure calculations and atomistic simulations is a clear asset, as well as experience with machine learning, specifically neural networks, statistical learning and/or Gaussian processes, and computer languages such as Python and C.

The position requires good communication skills in written and spoken English. If you do not have English or a Scandinavian language as your mother tongue you need to provide documentation of  good communication skills in English, typically evidenced by an English language test, for example TOEFL 550 (paper-based)/TOEFL 213 (computer-based), and/or exemplified during the interview process prior to admission.

Contract terms
Full-time temporary employment. The employment is composed of a maximum of four years full-time of doctoral studies plus a maximum of one year of computational user support within atomic scale simulation, equivalent to a maximum of 20 % of the total working time. The employment is thus limited to a maximum of five years. The employment is tied to successful completion of department evaluations after one and three years.

We offer
Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg. 
Read more about working at Chalmers and our benefits for employees.

Chalmers aims to actively improve our gender balance. We work broadly with equality projects, for example the GENIE Initiative on gender equality for excellence. Equality and diversity are substantial foundations in all activities at Chalmers.

Application procedure
The application should be marked with Ref 20230127 and written in English. The application should be sent electronically and be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.

CV: (Please name the document: CV, Family name, Ref. number)
• CV
• Other, for example previous employments or leadership qualifications and positions of trust.
• Two references that we can contact.

Personal letter: (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

Other documents:
• Copies of bachelor and/or master’s thesis.
• Attested copies and transcripts of completed education, grades and other certificates, e.g. TOEFL test results.

Please use the button at the foot of the page to reach the application form. 

Application deadline: March 24, 2023



For questions, please contact:
Prof. Paul Erhart, Condensed Matter and Materials Theory,
erhart@chalmers.se,
+46(0)31-772-3669

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***