Research Associate or PhD student for AI investigation of 2D polymers

PhD student
Salary: E 13 TV-L (up to €2700 net per month)
Employment begins:At the next possible date
Duration: up to 4 years
Contact: jobs.nano@tu-dresden.de
Cover
©CRC1415

The Faculty of Physics and the Faculty of Mechanical Science and Engineering, Institute of Materials Science, Chair of Materials Science and Nanotechnology offers a position as Research Associate/PhD student (m/f/x) (subject to personal qualification employees are remunerated according to salary group E 13 TV-L). The position comprises up to 100 % of the fulltime weekly hours and is limited to 36 months with the option of extension. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz – WissZeitVG) and offers the chance to obtain further academic qualification (usually PhD thesis). Balancing family and career is an important issue. The position is generally suitable for candidates seeking part-time employment. Please indicate your request in your application.

uploads/open_job/img/CRC_seminar_image_nOzRUHL.jpg
©CRC1415
Tasks

The aim of the research work within the Collaborative Research Center CRC1415 “Chemistry of synthetic 2D materials” is to combine quantum mechanical (QM) methods with state-of-the-art machine learning (ML) techniques to investigate and predict the electronic and magnetic properties of the building blocks in two-dimensional (2D) polymers (e.g., (a)chiral covalent organic frameworks) . This will enable us to define data-driven design rules that will be integrated into generative AI frameworks for the design of novel 2D polymers with desired QM properties for catalysis and energy storage. The computational work will be performed in close collaboration with synthetic chemists at TU Dresden to validate the synthesis of the novel materials, ensuring an interdisciplinary working environment. The project would require the candidate to perform extensive QM calculations using density functional theory and to develop python-based tools for data analysis. Additionally, further development of ML-based computational workflows to explore structure-property and property-property relationships will be a key task.

uploads/open_job/img/overview_application_CRC1415.jpeg
©TUD
Requirements

University degree in physics, chemistry, materials science, engineering or similar . Knowledge and practical experience in quantum mechanical methods as well as in machine learning approaches (force field development, generative models) are required. Previous hands-on experience with Fortran, Python, and PyTorch is highly desirable. Previous computational experience in research projects concerning organic molecules and materials is desirable, but not a prerequisite. A high degree of commitment, interdisciplinary thinking, the ability to work in a team and independently, as well as excellent communication and writing skills in English are required.

Please submit your detailed application containing your Curriculum Vitae (max. 4 pages), motivation letter (max. 1 page), transcripts of bachelor or master degree (in English or German), and a recommendation letter from a senior/junior research scientists, preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to jobs.nano@tu-dresden.de.

Further information

Please submit copies only, as your application will not be returned to you. Expenses incurred in attending interviews cannot be reimbursed.

Mail contact
TU Dresden
Faculty of Physics and Faculty of Mechanical Science and Engineering
Institute of Materials Science
Chair of Materials Science and Nanotechnology
Prof. Dr. Gianaurelio Cuniberti
Hallwachsstr. 3, 01069 Dresden, Germany

Supervisor contact
Groups
Projects

Research Associate or PhD student for AI investigation of 2D polymers

PhD student
Salary: E 13 TV-L (up to €2700 net per month)
Employment begins:At the next possible date
Duration: up to 4 years
Contact: jobs.nano@tu-dresden.de
Cover
©CRC1415

The Faculty of Physics and the Faculty of Mechanical Science and Engineering, Institute of Materials Science, Chair of Materials Science and Nanotechnology offers a position as Research Associate/PhD student (m/f/x) (subject to personal qualification employees are remunerated according to salary group E 13 TV-L). The position comprises up to 100 % of the fulltime weekly hours and is limited to 36 months with the option of extension. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz – WissZeitVG) and offers the chance to obtain further academic qualification (usually PhD thesis). Balancing family and career is an important issue. The position is generally suitable for candidates seeking part-time employment. Please indicate your request in your application.

uploads/open_job/img/CRC_seminar_image_nOzRUHL.jpg
©CRC1415
Tasks

The aim of the research work within the Collaborative Research Center CRC1415 “Chemistry of synthetic 2D materials” is to combine quantum mechanical (QM) methods with state-of-the-art machine learning (ML) techniques to investigate and predict the electronic and magnetic properties of the building blocks in two-dimensional (2D) polymers (e.g., (a)chiral covalent organic frameworks) . This will enable us to define data-driven design rules that will be integrated into generative AI frameworks for the design of novel 2D polymers with desired QM properties for catalysis and energy storage. The computational work will be performed in close collaboration with synthetic chemists at TU Dresden to validate the synthesis of the novel materials, ensuring an interdisciplinary working environment. The project would require the candidate to perform extensive QM calculations using density functional theory and to develop python-based tools for data analysis. Additionally, further development of ML-based computational workflows to explore structure-property and property-property relationships will be a key task.

uploads/open_job/img/overview_application_CRC1415.jpeg
©TUD
Requirements

University degree in physics, chemistry, materials science, engineering or similar . Knowledge and practical experience in quantum mechanical methods as well as in machine learning approaches (force field development, generative models) are required. Previous hands-on experience with Fortran, Python, and PyTorch is highly desirable. Previous computational experience in research projects concerning organic molecules and materials is desirable, but not a prerequisite. A high degree of commitment, interdisciplinary thinking, the ability to work in a team and independently, as well as excellent communication and writing skills in English are required.

Please submit your detailed application containing your Curriculum Vitae (max. 4 pages), motivation letter (max. 1 page), transcripts of bachelor or master degree (in English or German), and a recommendation letter from a senior/junior research scientists, preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to jobs.nano@tu-dresden.de.

Further information

Please submit copies only, as your application will not be returned to you. Expenses incurred in attending interviews cannot be reimbursed.

Mail contact
TU Dresden
Faculty of Physics and Faculty of Mechanical Science and Engineering
Institute of Materials Science
Chair of Materials Science and Nanotechnology
Prof. Dr. Gianaurelio Cuniberti
Hallwachsstr. 3, 01069 Dresden, Germany

Supervisor contact
Groups
Projects