PhD Research Associate in Data-Driven Mechanics
Join a leading German university to develop innovative computational methods for mechanics research.
Best for:Best for engineering PhD candidates with expertise in computational mechanics, data analysis, and a passion for materials science research.
Overview
This PhD position at Technische Universität Braunschweig focuses on advancing data-driven mechanics within the Institute of Applied Mechanics. The role involves conducting cutting-edge research, contributing to teaching, and collaborating with a multidisciplinary team. Applicants will engage in computational modeling, data analysis, and experimental validation to address challenges in materials engineering. The position is ideal for candidates with a strong background in engineering, computational methods, or related fields, seeking to pursue a PhD while contributing to impactful research.
What you'll do
- Conduct independent research in the field of data-driven mechanics, focusing on computational methods and their application to materials engineering problems.
- Develop and implement computational models to simulate mechanical behavior of materials.
- Perform experimental validation of computational models to ensure accuracy and reliability.
- Collaborate with faculty and peers to advance research projects and publish findings in high-impact journals.
- Assist in teaching and mentoring undergraduate or graduate students as part of academic responsibilities.
- Present research findings at national and international conferences.
- Contribute to the development of innovative methodologies for data-driven mechanical analysis.
Requirements
Degree required: Master's degree in Mechanical Engineering, Materials Science, Applied Mathematics, or a related field
Degree offered: PhD
Language: English; proficiency at a level suitable for academic research and teaching
Instruction: English
- Strong background in computational mechanics or finite element methods
- Proficiency in programming languages such as Python, MATLAB, or C++
- Experience with data analysis and machine learning techniques
- Familiarity with experimental techniques in materials testing
- Excellent written and verbal communication skills in English
- Open to all nationalities
- No specific residency or age restrictions mentioned
Funding & terms
How to apply
Deadline: 2026-11-15 (Europe/Berlin)
Interested applicants should submit their application via the university’s internal portal. The application should include a CV, a letter of motivation, academic transcripts, and a research proposal outlining their interest and qualifications for the position.
- Curriculum Vitae (CV)
- Letter of motivation
- Academic transcripts (BSc and MSc)
- Research proposal (describing interest and qualifications)
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