The Foundations of Deep Learning Lab at Tel Aviv University's School of Computer Science is looking for excellent research students to help develop a mathematical theory behind deep learning.
Deep learning is experiencing unprecedented success in recent years, delivering state of the art performance in a multitude of application domains. However, despite its extreme popularity and the vast attention it is receiving, our formal understanding of deep learning is limited. Its application in practice is based primarily on conventional wisdom, trial-and-error, and intuition, often leading to suboptimal results (compromising not only effectiveness, but also safety, privacy and/or fairness).
The Foundations of Deep Learning Lab at Tel Aviv University's School of Computer Science is developing a mathematical theory behind deep learning, with the aim of shedding light on existing empirical findings, and more importantly, leading to principled methods that bring forth improved performance and new capabilities. The lab is headed by Dr. Nadav Cohen, and regularly publishes in top tier machine learning venues (e.g. NeurIPS, ICML, ICLR). Its research is highly mathematical, but also includes extensive empirical evaluations that support theory. For more information please visit: https://www.cohennadav.com/.
We are looking for:
You, an excellent mathematically inclined research student, to join us, and help crack open the black box of deep learning. Typical entry to the lab is at MSc level, with the option of pursuing a subsequent PhD if there is mutual interest. Entry at PhD level is also possible, but only in exceptional cases. If interested in applying, please verify that you meet the criteria below, and if so, include in your application CV and grade transcripts.
Prospective MSc students:
* BSc from a well-known university, with GPA of at least 95.0/100 (or equivalent), in one of the following disciplines: (i) Mathematics; (ii) Mathematics & Computer Science; (iii) Mathematics & Electrical Engineering; or (iv) Mathematics & Physics.
* Successful completion of introductory course in machine learning (Tel Aviv University's course #0368323501 or equivalent)
* Solid Python programming skills
* Willingness and ability to devote full-time to research
* High degree of independence, work ethic and creativity
* Experience with deep learning frameworks (e.g. PyTorch or TensorFlow)
* Professional (industry) experience in machine learning
Prospective PhD students:
In addition to the requirements above, applicants interested in joining at PhD level are expected to meet at least one of the following:
* Proven track record in machine learning research (with publication in top-tier venues)
* Advanced coursework and research in either of the following: Statistics, Optimization, Dynamical Systems, Numerical Analysis, Quantum Physics or Quantum Computing.