ACCESS is an independent research institute affiliated to RWTH Aachen University. 70 engineers and scientists work both in a fundamental and industry-oriented manner on issues relating to the primary forming of metallic materials. The focus is on casting processes, but additive manufacturing and joining techniques involving melting are also investigated. In its Techcenter, Access operates a state-of-the-art, semi-automated investment casting process chain for the production of precision-cast high-performance components used in aviation.
ACCESS is seeking to strengthen its Microstructural Simulation Group in the area of machine learning and the development of AI methods, particularly in combination with applications in computational mechanics. We are looking for a new team member to support our growing AI group.
We are an international team of researchers led by Dr.-Ing. Shahed Rezaei in Aachen, in close collaboration with colleagues from Munich and RWTH Aachen, dedicated to advancing the frontiers of artificial intelligence in computational mechanics. Our team is highly diverse, bringing together experts from various countries and disciplines. We focus on developing, implementing, and evaluating novel AI algorithms to drive progress in scientific machine learning. In particular, we are interested in integrating and extending the capabilities of well-established numerical methods such as FEM, FVM, FDM, and FFT-based techniques into an AI framework. Our work is regularly published in leading peer-reviewed journals, including CMAME, IJNME, JMPS, and npj Computational Materials. We maintain close collaborations with multiple institutes at RWTH Aachen University, as well as with academic and research institutions across Germany and around the world.
Your tasks and responsibilities:
We are seeking highly motivated candidates with a strong passion for research and a drive to contribute to cutting edge developments at the intersection of AI and computational mechanics. A forward-looking research mindset is a key priority for this position.
Specific areas of focus include:
• Strong interest in applying and advancing AI methods for scientific machine learning, particularly in the context of microstructural simulations
• Development and execution of finite element simulations, including nonlinear phenomena such as plasticity and damage and multiscale analysis
• Design and implementation of advanced deep learning architectures, especially in the areas of operator learning and physics-informed neural networks
• Training of deep learning models using the JAX framework on high-performance GPU clusters
• Evaluation, interpretation, and analysis of simulation results for advanced engineering materials, such as nickel-based superalloys used in the aviation industry
• Managing collaborations with our partner institutes at RWTH Aachen University and industrial partners.
Your qualifications:
• You hold (or are about to complete) a Master’s degree in Computational Mechanics, Mechanical Engineering, Civil Engineering, Materials Science/Engineering, Applied Mathematics, or a closely related field.
• You have solid knowledge of artificial intelligence and hands-on experience with machine learning applications.
• You are experienced with numerical simulation methods, ideally the finite element method (FEM) or similar techniques.
• You have a background in material modeling, such as plasticity and damage mechanics.
• You are skilled in software development and object-oriented programming, including the use of modern development environments and the creation of technical documentation.
• You have strong Python programming skills; C++ experience is a major advantage.
• You are fluent in English (both in communication and scientific writing); German skills are a plus—or you are open to learning the language.
Benefits / What we offer:
• You will join a highly motivated, international research team with expertise in AI, computational mechanics and material engineering working in a vibrant and supportive atmosphere with strong industry collaboration. You will be closely mentored by experts in the field. Our offices are located in the heart of Aachen, offering a stimulating work environment with excellent infrastructure.
• The position is research-focused, with minimal teaching responsibilities, allowing you to fully dedicate your time to scientific exploration. You will have the opportunity to present your work at international conferences, participate in summer schools, and benefit from voluntary exchange programs.
• Our team is embedded in a global research network, with collaborations across Japan, France, the U.S., and more. Research visits to our international partners can be arranged for successful candidates.
• Former team members have gone on to secure prestigious positions in both academia and industry.
• The position is initially DFG funded for three years, with the possibility of extension until the completion of your PhD (Full-time position with competitive salary based on the TVöD / TVL pay scale). The starting date is flexible and can be arranged to suit your availability.
• Flexible working options, including the possibility to work from home
• Opportunity to pursue a doctoral degree from RWTH-Aachen University
• Access e.V. is an equal opportunity employer committed to promoting diversity. We explicitly encourage female candidates and underrepresented groups to apply.
We look forward to receiving your application! To keep things simple, our application process is intentionally lightweight — we only ask for your CV and academic transcript. There is no need to submit a cover letter, internship reports, or certificates at this stage.
Please send your documents by email only to: karriere@access-technology.de Deadline: July 31, 2025
If you have any questions, Dr.-Ing. Shahed Rezaei (s.rezaei@access-technology.de) will be happy to assist you
