Computational Statistics: upcoming seminars, recordings and deadlines

This week

All 2 upcoming talks

Closes today

Oct 14

ERC Starting Grant

European Research CouncilOpen to all fields

Opportunities

Career stage

All 14 funding calls

Closes Nov 30

CAPES-Humboldt Research Fellowship — Call 27

CAPES and Alexander von Humboldt FoundationOpen to all fields

Closes Dec 2

Canada Graduate Research Scholarship – Master’s program

CIHR, NSERC and SSHRCOpen to all fields

Closes Jan 12, 2027

ERC Consolidator Grant 2027

European Research CouncilOpen to all fields

Conferences and workshops

All 7 upcoming workshops

Nov 2–6, 2026

Causal AI Methods for Computational Biology

Nov 16–20, 2026

Metabolomics with R/Bioconductor

Nov 30 – Dec 4, 2026

Bayesian Methods for Biomedical Data Science

Dec 1–4, 2026

Introduction to Occupancy Models with R

People

All people in Computational Statistics

Himel Mallick
Cornell University, USA · as of Nov 2026
Next: Causal AI Methods for Computational Biology · Nov 2
Ivo D. Dinov
University of Michigan — SOCR, DCMB and MCAIM · as of Sep 2026
Latest: The Realities of Augmented Intelligence · Sep 30, 2026
Arka Banerjee
Indian Institute of Science Education and Research Pune · as of Jun 2026
Latest: Harnessing information from higher order statistics in cosmology - k-nearest neighbor (kNN) distributions · Jun 2, 2026
Charlie Gao
Posit · as of Oct 2026
Next: Async and Parallel R: Building the Open Source Tools · Oct 22, 2026
Pietro Franceschi
Fondazione E. Mach, Italy · as of Nov 2026
Next: Metabolomics with R/Bioconductor · Nov 16
Natalie Karavarsamis
University of Melbourne, Australia · as of Dec 2026
Next: Introduction to Occupancy Models with R · Dec 1

On demand

All 5 recorded talks All 2 ePosters

Tue, Jun 2 · 15:00 UTC

Harnessing information from higher order statistics in cosmology - k-nearest neighbor (kNN) distributions

Arka Banerjee · Indian Institute of Science Education and Research PuneVideo · 1 h

Fri, Mar 18, 2022

Diverse covariates modulate neural variability: a widespread (sub)cortical phenomenon

David Liu,Theoklitos Amvrosiadis,Nathalie Rochefort,Máté Lengyel

Fri, Nov 18, 2022 · 19:00 UTC · Online

Network inference via process motifs for lagged correlation in linear stochastic processes

Alice Schwarze · Dartmouth CollegeVideo · 1 h 23 min

Thu, Mar 17, 2022

Bayesian Inference in High-Dimensional Time-Series with the Orthogonal Stochastic Linear Mixing Model

Rui Meng,Kristofer Bouchard

New and updated

Jan 25–29, 2027

Ecological Forecasting in Practice: Building Iterative Workflows for Biodiversity Predictions

Dec 10–18, 2026

Geometric Morphometrics in R

Dec 7–10, 2026

Generalised Additive Models in R

Fri, Oct 16, 2020 · 15:00 UTC · Online

Theoretical and computational approaches to neuroscience with complex models in high dimensions across multiple timescales: from perception to motor control and learning

Surya Ganguli · Stanford UniversityVideo

Nearby fields

All fields