PhD positions in Machine Learning
Laboratory for Information and Inference Systems at Ecole Polytechnique Federale de Lausanne (EPFL) is currently looking for multiple PhD students in Machine Learning.
There are two positions that revolve around the following topics:
We would like to develop robust reinforcement learning techniques based on optimization and sampling techniques. Inverse reinforcement learning and imitation learning are also of interest.
Besides, candidates’ experience on learning theory, sampling, and statistics are also encouraged.
The LIONS lab provides a fun, collaborative research environment with state-of-the-art facilities at EPFL, one of the leading technical universities worldwide. EPFL is located in Lausanne next to Lake Geneva in a scenic setting with excellent transport connections. The working language at EPFL is English.
Successful applicants need to be highly motivated, excellent students with a solid background in information theory, optimization, computer science, or applied mathematics. Advanced coding skills is a big plus.
Candidates should directly apply to the EDEE or EDIC doctoral programs and list Prof. Volkan Cevher as a potential host for their PhD studies.
For more details please check: http://phd.epfl.ch/application.
The working language at LIONS is English.
Starting date: Continuous
Informal inquiries should be sent to Gosia Baltaian, [email protected].
The Laboratory for Information and Inference Systems (LIONS) at EPFL is looking for postdoctoral fellows with a strong background in machine learning, continuous optimization, and deep learning, or other related areas to work under the supervision of Prof. Volkan Cevher. Strong coding skills is a big plus.
There are three positions that revolve around the following topics around LLMs or VLMs:
- Rethinking robustness in deep learning to enhance and verify robustness of models.
- Continuous and discrete optimization theory to develop new continual learning, federated learning, and combinatorial optimization methodology.
- Accelerating inference systems to build next generation inference frameworks.
In addition to theory background, candidates with computer vision or other application backgrounds are encouraged to apply. Candidates can also participate at several interesting applications projects with big tech, imaging, communications, and finance companies within our laboratory.
LIONS provides a stimulating, collaborative, and fun research environment with state-of-the-art facilities at EPFL.
Our group is quite active in premiere ML venues, including NeurIPS, ICML, and ICLR. Personal initiative and independent research tasks related with the candidate’s interests are also encouraged.
Among our postdoc alumni, twelve took professor positions (University of Wisconsin, Warwick University, University of Oslo, Linkoping University, Technion University, Umea University, Zhejiang University, Vietnam National University, National University of Singapore, University of North Carolina, AIMS South Africa, and CU-Boulder). One is leading an AI team at SwissRe and the others took postdoctoral or scientist positions at McGill and Alan Turing Institute.
Among our PhD alumni, five became professors (University British Columbia, UCL, Umea University, National Taiwanese University, and Rice University). Two are engineers at Kandou Bus. Five took scientist positions at Square Point, Meta, SDSC, Samsung AI and UnternehmerTUM. Others took postdoc positions at UT Austin, ETHZ (2), CIBM, and UniGE.
The working language at EPFL is English.
For the postdoctoral positions, candidates should have or be close to finishing a PhD degree in electrical engineering, computer science, applied mathematics, or a related field. Candidates should send their CV, a research statement outlining their expertise and interests, any supplemental information, and a list of at least three references with full contact information to the LIONS Lab Administrator:
Gosia Baltaian ([email protected])
EPFL STI IEL LIONS
ELD 244 (Bâtiment ELD)
Informal enquiries can also be sent to Gosia Baltaian, [email protected].