Doctoral Position in Machine Learning for Engineering Design 100%

ETH Zürich; Zürich; In loco; CHF 55.000 - 75.000; Tempo pieno

Vantaggi offerti da questo lavoro

Career development

Mentoring and growth

Diverse team

Descrizione del lavoro

ETH Zürich's IDEAL Lab invites applications for one to two doctoral positions in Machine Learning for Engineering Design under Prof. Mark Fuge. This general search prioritizes scientific excellence and fit to the lab with focus areas spanning ML, optimization, robotics and design challenges.

You will conduct independent or collaborative research, publish findings, and collaborate with industry, academia, and national labs while pursuing relevant coursework and mentoring students.

Competenze

• Open to diverse educational backgrounds (engineering, mathematics, CS, physics or others).
• Interest or expertise in ML, optimization, simulation or robotics.
• Strong publication record is a plus but not required, especially for non-traditional paths.
• Experience with HPC environments or software engineering is a plus but not required.
• Strong English language skills and ability to collaborate in multinational teams.

Mansioni

• Conduct individual or collaborative research, write publications and contribute to code bases.
• Collaborate with industry, academia, and national labs to translate real-world needs into questions.
• Learn new graduate courses or via self-learning to extend skills.
• Assist with the lab’s teaching mission and supervise Master/Bachelor thesis students as needed.
• Support shared administrative tasks and contribute as a good lab citizen.

Conoscenze

Machine Learning

Optimization

Simulation

Robotics

Descrizione del lavoro

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.

• 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 or Software Engineering best practices is a plus, but not a requirement
• You should possess strong English language skills and the ability to work successfully and collaboratively on diverse, multinational teams

We 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.

We offer

You can look forward to:

• World-class research infrastructure and excellent working conditions guided by our common understanding of a supportive shared work culture
• Opportunities to work with a diverse, motivated and multicultural team in a creative research environment
• An rich intellectual environment within the lab and the university that includes top scholars from across the globe
• Support 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 R&D

Working, teaching and research at ETH Zurich

We value diversity and sustainability

In 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.

Curious? So are we.

We look forward to receiving your online application with the following documents in PDF format (make sure your last name is on all the documents and in the file name):

• A Curriculum Vitae or Resume detailing your relevant past experience including a list of publications (if relevant)
• A Research Statement or Statement of Purpose describing why you are interested in pursuing a Ph.D. position (and in our lab in particular), what types of research topics related to the lab would interest you and what background or past experience you have that makes you well suited for those topics. (1-2 pages)
• A copy of your undergraduate and graduate transcripts
• A short Cover Letter listing possible time windows you would be available during the weeks of January 25th and February 1st for a Zoom interview, as well as your desired start date. This is to help us facilitate logistics and scheduling for the Zoom interviews, and will not affect candidate evaluation
• Contact information for two references, which can be appended to the CV or provided as a separate PDF if you prefer. No reference letters are needed at the time of application, and we will notify you in advance if we intend to reach out to them or request letters

Further information about our lab can be found on our Website.

Questions regarding the position should be directed to Mrs Martina Koch, Adm. Assistant, Tel [phone] or [e-mail] (no applications).

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

For best consideration, please submit the above application by January 15th, 2027. We anticipate providing interviews and final decisions to candidates before March 1st. The start date can be determined upon mutual agreement with the selected candidate(s) to best account for their personal needs, but as a range we anticipate that the earliest start date could be during May 2027, with the latest start date being October 2027.

We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.