Computational Physics

Paco Villaescusa surveys the growing role of numerical simulations and AI in cosmology. Quijote and Backlight explore how much information about the Universe can be recovered beyond conventional summary statistics, including nonlinear structure and higher-order relationships. CAMELS addresses uncertainty in galaxy formation and other astrophysical processes, while DREAMS examines dark-matter predictions in the presence of baryonic effects. The seminar then considers automated research workflows through Denario, a system that develops hypotheses, plans analyses, writes and executes code, and interprets results. It discusses possibilities opened by combining simulation libraries with coordinated AI systems, while framing these as research directions. The speaker is a computational cosmologist at the Flatiron Institute.

Lurdes Ondaro Mallea examines whether current models of the kinematic Sunyaev–Zeldovich signal accurately recover diffuse baryons and the strength of astrophysical feedback. The analysis uses hydrodynamic simulations to generate mock stacked measurements for realistic DESI-like galaxy samples, separating contributions from gas density, velocities and nonlinear astrophysics. It tests baryonic changes to density and velocity fields, satellite galaxies, nonlinear velocities and velocity reconstruction. Neglecting satellites can underestimate halo gas fractions at today's measurement precision; further corrections become significant for future datasets. The talk explains how including these effects can improve gas-distribution measurements and assessments of feedback. Online via Zoom. Monday 28 September 2026, 11:00–12:00 PDT (America/Los_Angeles; UTC−7). Follow Join the zoom meeting on the organizer's event page. Lurdes Ondaro Mallea is affiliated with Cambridge. Organized by the Kavli Institute for Particle Astrophysics and Cosmology (KIPAC), Stanford University. This listing advertises the verified remote option.

Richard Huang investigates how DNA nanostructures deform under uneven hydrodynamic forces, a question relevant to drug delivery, vaccines and biosensors. Coarse-grained molecular dynamics and mechanical models first examine linear and circular DNA in extensional flow. Drag concentrates tension near the middle of linear duplexes, disrupting base pairs and causing overstretching. Deforming minicircles straighten along their sides while concentrating bending into opposing tips and localized kinks. Models based on DNA elasticity and hydrodynamic-force distributions explain these responses, then extend to wireframe DNA origami to study force transmission and how local structural transitions produce whole-particle deformation. The results inform structures designed for stability or controlled deformation in flow. Online via Zoom. Friday 2 October 2026, 12:00–13:00 EDT (America/New_York; UTC−4). Open the Zoom link on the official event page; the audience explicitly includes the public. Richard Huang is affiliated with MIT. Organized by MIT Department of Mathematics — Computational Research in Boston and Beyond Seminar.

The IAU General Assembly brings together the international astronomy community for symposia, focus meetings and broader scientific exchange. The preliminary programme includes computational astrophysics, CTAO, planet formation, stellar populations, low-surface-brightness astronomy and AI methods. Registration opened on 15 September 2026. Standard talk/poster abstracts and participation-grant applications close on 15 January 2027; early registration closes on 5 March. Session details remain subject to confirmation.

Develop data formats and compression methods for CMS real-time event reconstruction at rates up to 750 kHz. The role combines accelerator-friendly data structures, CPU/GPU performance studies, evaluation of information loss and AI-assisted compression while preserving useful physics information. This on-site appointment lasts 24 months, potentially extending to 36, with a target start of 1 January 2027. Applications close on 25 September 2026 at 23:59 Geneva time. Applicants need a relevant master’s with two to six years of subsequent experience, or a PhD with at most three years, and must not previously have held a CERN fellow or graduate contract. Apply using the employer’s linked form with a CV and relevant diploma.

The University of Cambridge's Handley Lab seeks a researcher to connect fundamental theories with cosmological and astrophysical observations using AI-assisted scientific software and GPU-accelerated inference. The role includes developing physical predictions, Bayesian methods including nested sampling, publishing research and shaping an independent research programme. The post is based at the Kavli Institute for Cosmology and Institute of Astronomy, with funding initially available until 30 September 2030. Appointment is at Grade 7 or Grade 9 according to experience; Grade 9 requires Faculty Board approval. Salary: £37,694–£59,966. Applications close on 25 September 2026 at 23:59 GMT, as stated by the employer. Submit a cover letter, CV, publications, research statement, evidence of computational skills and two academic referee contacts through the university recruitment system. A PhD, completed or near completion, in physics, astronomy, applied mathematics or a related field is required. Reference LG51052.

Develop software and analysis tools for beam-optics measurements and corrections within the High-Luminosity Large Hadron Collider project; requires Python expertise and preferably knowledge of accelerator physics.

CERN's CMS experiment is recruiting a scientist to deliver near-real-time, offline-quality detector calibrations for the High-Luminosity LHC High-Level Trigger. The role maintains the Next-Generation Trigger demonstrator, develops calibration algorithms with CMS detector and physics-object groups, designs a production data-acquisition and calibration system, and tests its integration and physics performance. The 24-month hybrid appointment is based in Geneva with an ideal start date of 1 January 2027. Applications close on 5 October 2026 at 23:59 Geneva time.

Develop algorithms and research software for quantum many-body science, including work associated with packages such as TRIQS, AFQMC and ITensor. The fellowship joins the Center for Computational Quantum Physics and combines scientific research with software development and collaboration. The initial appointment lasts two years, with possible renewal for a third, starting between August and early November 2027. Annual salary is USD 95,000. Applications remain under consideration until filled; the priority date is 9 October 2026. Submit a CV/publications, a software and algorithm statement of at most four pages, and three confidential references through Interfolio.

Develop computational approaches to quantum many-body problems at the Center for Computational Quantum Physics. Research connects theory, numerical algorithms and scientific software with condensed matter, materials and quantum emulators. The initial appointment is two years, renewable for a third, with a start between August and November 2027. The annual salary is USD 95,000. Applications are reviewed until positions are filled; 9 October 2026 is a priority consideration date, not a final closing date. Apply through Interfolio with a CV/publications, research statement of at most four pages and three confidential reference letters.

Develop data formats and compression methods for CMS real-time event reconstruction at rates up to 750 kHz. The role combines accelerator-friendly data structures, CPU/GPU performance studies, evaluation of information loss and AI-assisted compression while preserving useful physics information. This on-site appointment lasts 24 months, potentially extending to 36, with a target start of 1 January 2027. Applications close on 25 September 2026 at 23:59 Geneva time. Applicants need a relevant master’s with two to six years of subsequent experience, or a PhD with at most three years, and must not previously have held a CERN fellow or graduate contract. Apply using the employer’s linked form with a CV and relevant diploma.

The Simons Foundation invites two-year research proposals that use Empire AI's multinode GPU clusters to address fundamental questions in computational astrophysics and physics, computational biology, mathematics, neuroscience or computational physical chemistry. Proposals must develop and use foundational machine-learning models for the scientific problem; data curation may be considered only when the resulting data are used to solve scientific problems within the same proposal. The programme expects to fund six to twelve awards from a total budget of six million US dollars.