Senior Faculty Position – Machine Learning

The Faculty of Engineering’s Signal Processing Track and Information Processing and Data Science Program is currently recruiting researchers in Machine Learning for a tenure-track position at Assistant and Associate Professor levels. We are seeking for candidates with strong theoretical background in machine learning, including, but not limited to: machine learning theory and algorithms; deep learning; unsupervised learning; statistical inference and learning; reinforcement learning; optimization; statistical relational learning; big data analytics; and machine learning and analytics applied to real-world problems e.g. speech, vision, and robotics.

We are especially interested in candidates who can contribute to the Faculty’s divers disciplines through their research, teaching, and services.
Candidates must exhibit excellent oral and written communication skills, an aptitude for teamwork, and scholarly interest in high-quality engineering education and research.

Faculty members are expected to supervise graduate students towards MSc and PhD degrees, conduct high-quality research, publish in top-level international journals and conferences, attract funding from competitive grants as well as from industrial and governmental bodies, and teach undergraduate and graduate courses in Hebrew and English.
We are also seeking candidates with collaborative potential or experience with other knowledge areas such as Life Sciences, Finance, Social Sciences and Humanities.

Requirements:

• A PhD in Electrical Engineering, Computer Engineering, Computer Science, Mathematics or a related field.
• Post-Doctoral training abroad in a well-known academic institute.
• Applications should be emailed to Ms Dina Yeminy, Faculty Administrative Head  ([email protected]), and to Prof. Sharon Gannot, Head of the Signal Processing Track ([email protected]).

Applications should include the following documentation:

1. Statement of Purpose (in English) indicating the applicant’s relevant qualifications and teaching plans.
   Note: plans should be specific, including methods of transferring knowledge and background to undergraduate and graduate students.
   Curriculum Vitae.
2. Statement of Research plan.
3. Statement of the Teaching plan.
4. References (from PhD Advisors, Post-doc advisors, and others familiar with the candidate’s work).

Within one month of applying (emailing the full set of documents), the applicant will be contacted. Should the initial screening be successful, the candidate may be asked to give a lecture about her/his current research topics and be interviewed by the Faculty Dean and Bar-Ilan Faculty members. If necessary, interviews can be conducted by electronic means.