Speculative Application for the Machine Learning group F/M

About Idiap

Idiap is an independent, not-for-profit, research institute accredited and funded by the Swiss Federal Government, the State of Valais, and the City of Martigny.

Idiap offers competitive salaries and working conditions at all levels in a dynamic, multicultural environment. Idiap is an equal opportunity employer. We specifically encourage women and minorities to apply.

Idiap is located in the town of Martigny in Valais, Switzerland, offering exceptional quality of life, exciting recreational activities, including hiking, climbing and skiing, as well as varied cultural activities. It is within close proximity to Lausanne and Geneva. Although Idiap is located in the French part of Switzerland, English is the official working language.

For frequently asked questions (FAQs) about living in Switzerland, please go to https://www.idiap.ch/en/faq

Job description

The Machine Learning group is always open to speculative applications for the following positions: postdocs, PhD and internship. There is no specific deadline, applications can be submitted at any time.

In addition to the usual CV, we strongly encourage applicants to clearly identify how they could contribute to our activities. Applications providing a clear research plan (one page maximum) are also very much encouraged and will be given full attention.

For PhD's
Appointments as a PhD student are typically for 4 years, conditional to successful progress, and should lead to a PhD dissertation, granted by the “Ecole Polytechnique Fédérale de Lausanne (EPFL)”. A PhD first year annual gross salary starts 47’040.- CHF.

Working at Idiap in Martigny, the successful candidate will become a doctoral student at EPFL, and thus also has to be accepted for enrolment by the Electrical Engineering Doctoral School (EDEE) or the Computer, Communication and Information Sciences Doctoral School (EDIC) before joining Idiap.


For postdocs
Postdoc appointments are typically for one year, with possibilities of renewal for a maximum of 4 years, conditional to performance. A postdoc first year annual gross salary starts at 80’000.- CHF .


For internships
Our internships usually last a few months and are paid.

Sought profile

For PhD's
The ideal Ph.D student should have a master (or equivalent) degree in engineering, physics, applied mathematics or similar. Graduates of neuroscience programs would also be well qualified. S/he should have a good background in mathematics, statistics, and programming. In order to balance the group, we especially encourage female applicants. However, all applications will be judged on merit.
The student will be registered at EPFL and located at Idiap.

For postdocs
The Postdoc candidate will work under supervision of one of senior researchers at Idiap, together with other colleagues from the machine learning group.
The Postdoc candidate should hold a PhD in relevant fields, while demonstrating excellence and motivation in research in general, and in the targeted research areas. A background in one of the following relevant fields - statistics, applied mathematics, optimization, linear algebra - is expected.
Applicants should have a track record of publishing at top-tier conferences or journals in machine learning, computer vision, or natural language processing. Applicants should also have strong programming skills and be familiar be familiar with *machine learning libraries* and with the Linux enviroment.

For internships
The ideal candidate should follow a M.Sc. program or hold a M.Sc. degree in computer science, electrical engineering or related fields. She or he should have a background at least in one of the following fields: statistics, applied mathematics, linear algebra.
Applicants should have existing hands-on experience in machine learning. They should also have strong programming skills and be familiar with the Linux environment.

In order to avoid discrimination, please do not mention your gender, age and marital status on your CV.

Required languages

• English - Level advanced

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