Materials Science Researcher

vor 3 Wochen

Dresden, Sachsen, Deutschland Technische Universität Dresden Vollzeit

Position Overview: The Faculty of Mechanical Science and Engineering at the Institute of Materials Science is seeking a qualified individual for the role of Research Associate / PhD Student. This position is designed for those aiming to enhance their academic credentials, typically through a PhD program. The role is structured for a duration of 36 months, with potential for extension, and is suitable for candidates interested in part-time employment.

Key Responsibilities: The primary focus of this research position within the Collaborative Research Center CRC1415, titled Chemistry of Synthetic 2D Materials, is to integrate quantum mechanical (QM) methodologies with advanced machine learning (ML) techniques. The objective is to analyze and forecast the electronic and magnetic characteristics of foundational elements in two-dimensional (2D) polymers, such as chiral covalent organic frameworks. This research will facilitate the establishment of data-driven design principles that will be incorporated into generative AI frameworks for creating innovative 2D polymers with specific QM attributes, particularly for applications in catalysis and energy storage.

Collaboration with synthetic chemists will be essential to validate the synthesis of these novel materials, fostering an interdisciplinary research environment. The candidate will be responsible for conducting extensive QM calculations utilizing density functional theory and developing Python-based tools for data analysis. Additionally, the role will involve advancing ML-driven computational workflows to investigate structure-property and property-property correlations.

Qualifications: Applicants should possess a university degree (Master/Diploma) in physics, chemistry, materials science, engineering, or a related field. Proficiency and practical experience in quantum mechanical methods and machine learning techniques (including force field development and generative models) are essential. Candidates should demonstrate a strong commitment to interdisciplinary collaboration, possess excellent teamwork and independent working skills, and have outstanding communication and writing abilities in English. Familiarity with programming languages such as Fortran, Python, and PyTorch is highly advantageous. Previous computational experience in research projects related to organic molecules and materials is preferred but not mandatory.

Diversity and Inclusion: The institution is committed to promoting gender diversity in academia and research and encourages women to apply. It is recognized as a family-friendly university and offers support services for dual career couples. Applications from individuals with disabilities are welcomed, and priority will be given to equally qualified candidates with disabilities in accordance with applicable regulations.

Application Process: Interested candidates are invited to submit a comprehensive application, including a Curriculum Vitae (maximum 4 pages), a motivation letter (maximum 1 page), transcripts of their bachelor or master degree, and a recommendation letter from a research supervisor. All applications should be submitted as a single PDF file.

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