Postdoc in molecular modeling for data-driven materials discovery

Project description
Per- and poly-fluoroalkyl substances (PFAS) have long been used in various industrial applications due to their favorable chemical and thermal stability, water resistance, and electrical insulation. In particular, they are widely used in the process of semi-conductor manufacturing; however, due to recent evidence of their adverse environmental and health effects, regulatory agencies are increasingly tightening restrictions on PFAS usage and pushing for their eventual phase-out, spurring an urgent need for alternative compounds. As such, semiconductor manufacturers face the imminent need to align their manufacturing practices with these strict, new regulations. The development of new PFAS replacements which address the potential risks associated with them while maintaining their favorable chemical properties is one of the crucial problems facing humanity in the next decade.

To engineer PFAS replacements for use in surfactants for etching solutions during semiconductor manufacturing, we must better understand what factors lead to their unique molecular properties, namely, their low surface tension in liquid-liquid interfaces. Because of this, PFAS are ideal surfactants which enable surface coat uniformity and improved line roughness during the semiconductor manufacturing process. However, surface tension is particularly challenging to model computationally due to the long time-scales and sensitivity to simulation parameters needed. Obtaining a better understanding of how molecular structure is related to surface tension can thus help design PFAS replacements with equivalent or better wetting characteristics than the currently used PFAS, but without the detrimental health and environmental effects.

For this project, the postdoctoral researcher will develop a molecular dynamics (MD) approach to modelling crucial chemical properties of PFAS replacement materials with a special focus on predicting surface tension. Surface tension can then be used to predict other relevant properties to surfactant development, such as the critical micelle concentration and wetting ability. This approach will be used to create an ML-ready dataset, which can be used to build various AI-driven QSPR models for computational prediction of these material properties. With a quick way to accurately predict surface tension for new molecules, the QSPR model can be used as a reward function for a reinforcement learning agent aimed at designing potential PFAS-replacement compounds.

This project is part of a collaboration between the AI Laboratory for Biomolecular Engineering, led by Dr. Rocío Mercado at Chalmers, and the Intel-Merck AWASES Program, a joint academic research center between Intel and Merck with the goal of accelerating sustainable semiconductor manufacturing processes.

Information about the division and the department
The AI Laboratory for Biomolecular Engineering (AIBE) is based in the division of Data Science & AI (DSAI) in the Department of Computer Science and Engineering (CSE). Led by Dr. Rocío Mercado, our group uses methods from machine learning and the life sciences to understand how molecules interact to form complex systems, and how we can use these insights to engineer molecular systems for therapeutic applications. We are currently focused on applying our computational tools to improving the understanding and design of molecular systems for drug discovery and materials applications. We interact closely with leading academic and industrial groups in computational chemistry, bioinformatics, materials science, and computer science. In AIBE, we seek to create a vibrant and collaborative environment where students and postdocs are supported in their pursuit of challenging research questions at the forefront of machine learning and the molecular sciences.

The CSE department is a joint department at Chalmers University of Technology and the University of Gothenburg, with activities on two campuses in the city of Gothenburg. The department is divided into four divisions, and employs around 270 people from over 30 countries. Research in the department has a wide span, from theoretical foundations to applied systems development. We provide high quality education at the bachelor’s, master’s, and graduate levels, offering over 120 courses each year. We also have extensive national and international collaborations with academia, industry and society.

Our aim is to actively improve our gender balance in both our department and division. We therefore strongly encourage applicants from historically-excluded groups to our positions, such as women and non-binary individuals. As an employee of Chalmers and CSE department, students are given the opportunity to contribute to our active work within the field of equality and diversity.

Major responsibilities
The major responsibilities for a postdoctoral researcher in the division include designing and carrying out cutting-edge research projects. Incoming postdocs should be able to identify novel research directions and design the appropriate computational experiments to answer those key questions, while being motivated to build expertise in an area complementary to their PhD. Postdocs are expected to effectively communicate the results of their research verbally and in writing, and will receive specific training towards honing these skills if desired.

While the working time of postdoctoral researchers is mainly devoted to research, this position also includes teaching at Chalmers’ undergraduate level, or performing other teaching duties corresponding to 20% of working hours (e.g., mentorship of master students). The appointment is a full-time employment for a period of not more than 3 years (2+1), funded by the Intel-Merck AWASES program.

Qualifications
A PhD in Computational Chemistry, Materials Science, or related fields is required before the start of the appointment. Previous research experience in molecular simulations and/or machine learning strongly preferred. The applicant should have previous programming experience, preferably in Python. Previous experience in Generative AI is a merit, but not required.

To qualify for the position of postdoc, you must hold a doctoral degree awarded no more than three years prior to the application deadline (according to the current agreement with the Swedish Agency for Government Employers).
The position requires sound verbal and written communication skills in English. Swedish is not a requirement but Chalmers offers Swedish courses.

You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education.

Contract terms
This postdoc position is a full-time temporary employment for 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 20240035 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 as: CV, Surname, Ref. number) including:
• CV, include complete list of publications
• Previous teaching and pedagogical experiences
• 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 research fields and main research results
• Describe your future goals and future research focus

Other documents:
• Attested copies of completed education, grades and other certificates.

Use the button at the foot of the page to reach the application form.

Application deadline: 2024-03-05

For questions, please contact:
Assistant professor Rocío Mercado, Data Science & AI division,
[email protected], +45 76 854 7752

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

Chalmers University of Technology conducts research and education in engineering sciences, architecture, technology-related mathematical sciences, natural and nautical sciences, working in close collaboration with industry and society. The strategy for scientific excellence focuses on our six Areas of Advance; Energy, Health Engineering, Information and Communication Technology, Materials Science, Production and Transport. The aim is to make an active contribution to a sustainable future using the basic sciences as a foundation and innovation and entrepreneurship as the central driving forces. Chalmers has around 11,000 students and 3,000 employees. New knowledge and improved technology have characterised Chalmers since its foundation in 1829, completely in accordance with the will of William Chalmers and his motto: Avancez!

URL to this page
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