Doctoral Position in Machine Learning for Engineering Design

**Doctoral Position in Machine Learning for Engineering Design** ================================================================ #### **100%, Zurich, fixed-term** The Laboratory for Intelligence in Design Engineering and Learning (IDEAL) in the Department of Mechanical and Process Engineering invites applications for one to two doctoral (Ph.D.) positions in the area of Machine Learning for Engineering Design under the guidance of Prof. Mark Fuge, the Chair of Artificial Intelligence in Engineering Design. The general area of the laboratory covers the study of Artificial Intelligence and Machine Learning in the context of Engineering Design problems in domains such as healthcare, power generation, aerospace, and robotics. **Project background** ---------------------- This is a general search and is not specific to a particular project so we are prioritizing scientific excellence and fit to the laboratory over any particular topic area. General areas of current research interest for the lab include, but are not limited to: * Self-Supervised Learning and Transfer Learning * Industrial Robotics and multi-robot coordination, particularly Design for Robotic Assembly/Manufacturing * Agentic/Multi-Agent coordination for Engineering Design * Formal Systems and Program Analysis * Intersection of Mathematical Topology and Machine Learning * Development of Engineering Benchmarks or Evaluation Frameworks * Other emerging areas at the intersection of ML/AI and Engineering Design **Job description** ------------------- As a Doctoral researcher, your responsibilities may include: * Individual or collaborative work on research including writing publications and contributing toward individual or shared code bases * Collaborating, where relevant, with partners from industry, academia, and national labs to translate real-world needs into scientific or technical questions * Learning new skills in specialized graduate areas via courses and other educational offerings, or through self-learning * Assisting with the teaching mission of the laboratory, which includes working with Masters and/or Bachelors thesis students as well as course assistance as needed * Generally being a good lab citizen by assisting in various shared laboratory administrative tasks shared by the team **Profile** ----------- The following are some characteristics that may align well with the position: * We are open to diverse educational backgrounds of applicants which can include engineering, mathematics, computer science, physics or other degree backgrounds * Students in the lab typically have interests in or expertise in one of the following areas: Machine Learning, Optimization, Simulation or Robotics * Having a strong publication record across either competitive journals or Computer Science conference venues is a plus, but not a requirement, especially for those with practical experience or non-traditional career paths * Experience with High-Performance Computing (HPC) environments