Topic: Data-sci

This seminar discusses a proof-of-concept gravitational-waveform model described in arXiv:2511.10522. It augments post-Newtonian equations using physics-informed neural-network methods and universal differential equations. The talk also covers ongoing development of a precessing surrogate model designed to evaluate in less than one millisecond while covering a broader portion of the LVK frequency band.

Develop an AI-assisted digital platform for stroke rehabilitation at the Singapore-ETH Centre. The project combines a mobile app and conversational agent with a soft robotic hand orthosis, supporting rehabilitation adherence at home. Work includes gathering patient and clinician requirements, building and validating the app, integrating rehabilitation hardware, and evaluating the intervention in a six-week clinical study with NTU and Tan Tock Seng Hospital. This is a full-time, fixed-term PhD position. The current vacancy accepts online applications without a stated closing date; submit a cove

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 documen

Investigate immune regulation in sepsis, particularly neuroimmune and interorgan communication, using computational analyses of bulk and single-cell sequencing datasets. The project is funded by FAPESP and is expected to start in November 2026. The advertisement lists 31 October 2026 as its application deadline and states that review starts immediately and continues until the position is filled. Submit a CV, research-interest cover letter and contact details for two references to the investigator listed on the official page.

The FICOSS-AI project will develop an open-source pipeline integrating astrophysical models, spectral diagnostics and AI to study stellar populations and galaxy evolution. The fellow will combine machine learning, population-synthesis models and spectral-analysis tools, contribute to publications and mentor students technically. The expected start is 1 February 2027, or earlier if needed. Apply by 2 November 2026 with a CV, publication list and research-interest statement; two recommendation letters must be sent directly by referees as described on the official advertisement.