Computer Science

Salvatore Torquato gives a public lecture in the Simons Foundation's 2026 Randomness series, connecting the geometry of complex systems with random structures and applications across mathematics, computer science, physics and chemistry.

Seminar by Morten Kjaergaard (Niels Bohr Institute, University of Copenhagen) on rapid FPGA-based feedback for superconducting qubits, including sparse-sampling techniques and on-FPGA inference enabling millisecond-timescale T1 estimation, ~100 ms readout optimization, and over 74,000 consecutive recalibrations in closed-loop operation.

Deep networks are often thought of as black boxes. Their ability to encompass vast swathes of knowledge indeed makes them hard to explain. Yet many of their behaviours — generalization under overparametrization, grokking, OOD failures, neural scaling laws — recur across architectures and scales, and each, however surprising, can be reproduced and explained in controlled settings. I will review these efforts to identify and explain the universal phenomena of deep learning, and suggest that an LLM may amount to a sum of such tractable sub-phenomena, interpolative in nature. Finally, leaving scientific rigor aside, I'll argue that what separates this prosaic picture from the apparent magic of LLMs may well be the industrial scale of compute and human labour behind it, and that AGI in its deeper extrapolative sense may be much further away than claimed.

Researchers and practitioners will discuss mathematical foundations of data science, including high-dimensional geometry, dimensionality reduction, scalable algorithms, uncertainty and machine learning. The conference takes place in person at the Salt Palace Convention Center on 16–20 November 2026. Registration is open, with early rates through 19 October; abstract and travel-support deadlines have passed. Registration also covers the co-located SIAM Imaging Science and Data Mining conferences.

The Simons Foundation invites proposals to organize new symposium series in mathematics and theoretical physics, including theoretical computer science. Selected series may comprise up to three weeklong meetings with travel, lodging, and meals covered for participants, creating sustained time for collaboration on timely research problems.

Supports established institutes and research centers in mathematics and the physical sciences to strengthen contacts within the international scientific community; up to $750,000 (inclusive of 20% indirect costs) over a three-year award period, with up to ten grants each year.

NSF support for interdisciplinary collaborations developing mathematical and theoretical foundations for explainable, reliable, sustainable and trustworthy artificial intelligence.

NSF support for new engineering investigators at eligible non-R1 institutions to initiate research programs, build capacity and advance their careers.

RIKEN invites junior researchers with advanced mathematical, computational or information-technology skills to support research across its host laboratories, including AI for Science. Around five appointments are planned. Fellows primarily join the Research Engineer Enablement Office in Wako and also work with a host laboratory; annual contracts may be renewed for a maximum of three years. Applicants must first secure a prospective host’s agreement. Mandatory registration closes on 23 October 2026 at 17:00 JST; documents and two reference letters are due on 30 October at 14:00 JST. The listed deadline is the earlier mandatory registration stage. Employment must begin between 1 April 2027 and 1 January 2028. The call and submission instructions are currently open.

Join the Algorithms and Visualization Group in ETH Zurich’s Social Networks Lab to develop methods for football match and performance analysis. Research uses event and player-tracking data and includes collaboration with professional football stakeholders, teaching and student supervision, and development of an independent research agenda. The full-time appointment is initially intended for two years, with flexibility in starting date and duration. Apply online by 30 November 2026 with a CV and referee contacts, motivation letter, publication list and three key achievements, and degree documentation.

Researchers and practitioners will discuss mathematical foundations of data science, including high-dimensional geometry, dimensionality reduction, scalable algorithms, uncertainty and machine learning. The conference takes place in person at the Salt Palace Convention Center on 16–20 November 2026. Registration is open, with early rates through 19 October; abstract and travel-support deadlines have passed. Registration also covers the co-located SIAM Imaging Science and Data Mining conferences.

Supports research-based graduate degrees with three funded years over a five-year fellowship: an annual $37,000 stipend plus a $16,000 institutional education allowance, subject to funding. Applications are open. The displayed deadline is the first subject deadline: Life Sciences on 19 October 2026. Computing, materials, psychology and social sciences are due 20 October; engineering 22 October; chemistry, geosciences, mathematics, physics and astronomy 23 October. All applications are due at 8 pm Eastern Time. Reference letters are due 16 October at 8 pm Eastern Time.