Doctoral Position in Machine Learning for Engineering Design

h3Doctoral Position in Machine Learning for Engineering Design /h3 h3100%, Zurich, fixed-term /h3 pThe 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. /p h3Project background /h3 pThis 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: /p ul liSelf‑Supervised Learning and Transfer Learning /li liIndustrial Robotics and multi‑robot coordination, particularly Design for Robotic Assembly/Manufacturing /li liAgentic/Multi‑Agent coordination for Engineering Design /li liFormal Systems and Program Analysis /li liIntersection of Mathematical Topology and Machine Learning /li liDevelopment of Engineering Benchmarks or Evaluation Frameworks /li liOther emerging areas at the intersection of ML/AI and Engineering Design /li /ul h3Job description /h3 pAs a Doctoral researcher, your responsibilities may include: /p ul liIndividual or collaborative work on research including writing publications and contributing toward individual or shared code bases /li liCollaborating, where relevant, with partners from industry, academia, and national labs to translate real‑world needs into scientific or technical questions /li liLearning new skills in specialized graduate areas via courses and other educational offerings, or through self‑learning /li liAssisting with the teaching mission of the laboratory, which includes working with Masters and/or Bachelors thesis students as well as course assistance as needed /li liGenerally being a good lab citizen by assisting in various shared laboratory administrative tasks shared by the team /li /ul h3Profile /h3 pThe following are some characteristics that may align well with the position: /p ul liWe are open to diverse educational backgrounds of applicants which can include engineering, mathematics, computer science, physics or other degree backgrounds /li liStudents in the lab typically have interests in or expertise in one of the following areas: Machine Learning, Optimization, Simulation or Robotics /li liHaving 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 /li liExperience with High‑Performance Computing (HPC) environments or Software Engineering best practices is a plus, but not a requirement /li liYou should possess strong English language skills and the ability to work successfully and collaboratively on diverse, multinational teams /li /ul pWe encourage candidates to apply even if they do not think they possess every point above, particularly for candidates who may not have had access to certain development opportunities. We will work with any selected candidates to develop targeted competencies on a personalized basis. /p h3Workplace /h3 h3Workplace /h3 h3We offer /h3 pYou can look forward to: /p ul liWorld‑class research infrastructure and excellent working conditions guided by our common understanding of a supportive shared work culture /li liOpportunities to work with a diverse, motivated and multicultural team in a creative research environment /li liAn rich intellectual environment within the lab and the university that includes top scholars from across the globe /li liSupport for personalized professional development and mentoring with the ability to build a strong support network for your future career and be part of a laboratory with a strong track record of placing employees into competitive research positions, professorships and industrial RD /li /ul pWorking, teaching and research at ETH Zurich /p h3We value diversity and sustainability /h3 pIn line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate‑neutral future. /p h3About ETH Zürich /h3 pETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting‑edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow. /p