Professur oder Assistenzprofessur (Tenure Track) für Signal Processing and Machine Learning* (Departement Informationstechnologie und Elektrotechnik)
ETH Zürich
Prendre contact
Liens Importants
Offre >
Entreprise >
Professur oder Assistenzprofessur (Tenure Track) für Signal Processing and Machine Learning*
The Department of Information Technology and Electrical Engineering (www.ee.ethz.ch) at ETH Zurich invites
applications for the above-mentioned position.
The new professor is expected to focus on fundamental research in signal processing and machine learning at large.
Potential focus areas include machine-learning algorithms, signal recovery and restoration, message passing, graph
signal processing, coding theory and storage, adaptive filters, array processing, remote sensing, and time-frequency
analysis. Moreover, the research can extend into various applications, encompassing biomedical, image, acoustic,
speech, and radar signal processing. The ideal candidate also possesses an inclination toward hardware, software, and
system aspects, and establishes synergies with other research areas in the Department of Information Technology and
Electrical Engineering and more broadly at ETH Zurich.
The successful candidate must be committed to innovative and engaging teaching in both fundamental undergraduate-level
courses and advanced graduate-level courses in the areas of signal processing and machine learning. At ETH Zurich,
undergraduate-level courses are taught in German or English, and graduate-level courses are taught in English. The
ability to lead a research group is expected.
Assistant professorships have been established to promote the careers of younger scientists. ETH Zurich implements a
tenure track system equivalent to that of other top international universities. The level of the appointment will
depend on the successful candidate's qualifications.
ETH Zurich is an equal opportunity and family-friendly employer, values diversity, and is responsive to the needs of
dual-career couples.
Please apply online for Assistant Professor (Tenure Track) of Signal Processing and Machine Learning
Please apply online for Professor of Signal Processing and Machine Learning
Applications should include a curriculum vitae, a list of publications and projects, a statement of future research
and teaching interests, a description of the leadership philosophy, three key publications, a description of the three
most important achievements**, and a certificate of the highest degree. The letter of application should be addressed
to the President of ETH Zurich, Prof. Dr. Joël Mesot. The closing date for applications is 15 February 2025 .
*Die Berufungskommission hat ihre Tätigkeit bereits aufgenommen, Bewerbungen können grundsätzlich nachgereicht werden.
** Die ETH Zürich legt Wert auf eine qualitative Bewertung akademischer Leistungen. In diesem Sinne sind Sie gebeten,
eine kurze Beschreibung Ihrer drei wichtigsten Errungenschaften den Unterlagen beizufügen (maximal je eine halbe
Seite). Dies können neben Forschungsergebnissen auch besondere Leistungen in der Lehre und deren Weiterentwicklung,
Dienstleistungen zugunsten der akademischen Gemeinschaft oder der Gesellschaft, Softwareentwicklungen, Patente,
Wissens- und Praxistransfer, Spin-offs und dergleichen sein.
Bitte beachten Sie: Alle Unterlagen sind in Englisch einzureichen.
The Department of Information Technology and Electrical Engineering (www.ee.ethz.ch) at ETH Zurich invites
applications for the above-mentioned position.
The new professor is expected to focus on fundamental research in signal processing and machine learning at large.
Potential focus areas include machine-learning algorithms, signal recovery and restoration, message passing, graph
signal processing, coding theory and storage, adaptive filters, array processing, remote sensing, and time-frequency
analysis. Moreover, the research can extend into various applications, encompassing biomedical, image, acoustic,
speech, and radar signal processing. The ideal candidate also possesses an inclination toward hardware, software, and
system aspects, and establishes synergies with other research areas in the Department of Information Technology and
Electrical Engineering and more broadly at ETH Zurich.
The successful candidate must be committed to innovative and engaging teaching in both fundamental undergraduate-level
courses and advanced graduate-level courses in the areas of signal processing and machine learning. At ETH Zurich,
undergraduate-level courses are taught in German or English, and graduate-level courses are taught in English. The
ability to lead a research group is expected.
Assistant professorships have been established to promote the careers of younger scientists. ETH Zurich implements a
tenure track system equivalent to that of other top international universities. The level of the appointment will
depend on the successful candidate's qualifications.
ETH Zurich is an equal opportunity and family-friendly employer, values diversity, and is responsive to the needs of
dual-career couples.
Please apply online for Assistant Professor (Tenure Track) of Signal Processing and Machine Learning
Please apply online for Professor of Signal Processing and Machine Learning
Applications should include a curriculum vitae, a list of publications and projects, a statement of future research
and teaching interests, a description of the leadership philosophy, three key publications, a description of the three
most important achievements**, and a certificate of the highest degree. The letter of application should be addressed
to the President of ETH Zurich, Prof. Dr. Joël Mesot. The closing date for applications is 15 February 2025 .
*Die Berufungskommission hat ihre Tätigkeit bereits aufgenommen, Bewerbungen können grundsätzlich nachgereicht werden.
** Die ETH Zürich legt Wert auf eine qualitative Bewertung akademischer Leistungen. In diesem Sinne sind Sie gebeten,
eine kurze Beschreibung Ihrer drei wichtigsten Errungenschaften den Unterlagen beizufügen (maximal je eine halbe
Seite). Dies können neben Forschungsergebnissen auch besondere Leistungen in der Lehre und deren Weiterentwicklung,
Dienstleistungen zugunsten der akademischen Gemeinschaft oder der Gesellschaft, Softwareentwicklungen, Patente,
Wissens- und Praxistransfer, Spin-offs und dergleichen sein.
Bitte beachten Sie: Alle Unterlagen sind in Englisch einzureichen.