# Mathematics 1,280 courses and talks. - [LLRF III](https://invisiblenetwork.ai/learn/cern/3014436): David McGinnis · CERN - [LLRF II](https://invisiblenetwork.ai/learn/cern/3014430): David McGinnis · CERN - [LLRF I](https://invisiblenetwork.ai/learn/cern/3019209): David McGennis · CERN - [The statistics of spins for CFTs](https://invisiblenetwork.ai/learn/cern/3011689): Nathan Benjamin · CERN - [Addressing the challenges of research data management, reuse and collaboration: the case for CERN Analysis Preservation and FAIR data services.](https://invisiblenetwork.ai/learn/cern/3016498): Sunje Dallmeier-Tiessen · CERN - [\[remote\] Big SAR Analysis Ready Data: Realizing the ESA-DLR Sentinel-1 Normalised Radar Backscatter Product](https://invisiblenetwork.ai/learn/cern/3005168): John Truckenbrodt · CERN - [Current status of the Data and Analysis Preservation effort in the PHENIX experiment](https://invisiblenetwork.ai/learn/cern/3005165): Maxim Potekhin · CERN - [Facilitating future open data reuse via continuous integration of actionable data analysis examples](https://invisiblenetwork.ai/learn/cern/3005169): Audrius Mecionis · CERN - [Non Linear Dynamics - Phenomenology I](https://invisiblenetwork.ai/learn/cern/3022767): Yannis Papaphilippou · CERN - [Non Linear Dynamics - Phenomenology II](https://invisiblenetwork.ai/learn/cern/3021688): Yannis Papaphilippou · CERN - [Non Linear Dynamics - Methods and Tools I](https://invisiblenetwork.ai/learn/cern/3022737): Yannis Papaphilippou · CERN - [Non Linear Dynamics - Methods and Tools II](https://invisiblenetwork.ai/learn/cern/3022735): Yannis Papaphilippou · CERN - [Applicability of hydrodynamics and role of the initial geometry (1/2)](https://invisiblenetwork.ai/learn/cern/2302746): Soeren Schlichting · CERN - [Applicability of hydrodynamics and role of the initial geometry (2/2)](https://invisiblenetwork.ai/learn/cern/2302747): Clemens Werthmann · CERN - [Nuclear geometry in UPCs](https://invisiblenetwork.ai/learn/cern/3000048): Bjoern Schenke · CERN - [Semiclassical analysis of finite cut-off JT gravity on a disk](https://invisiblenetwork.ai/learn/cern/3001601): Soumyadeep Chaudhuri · CERN - [Looping with combinatorics](https://invisiblenetwork.ai/learn/cern/3019597): Paolo Benincasa · CERN - [Demonstrating interactive, large-scale High Energy Physics data analysis workflows in distributed computing environments](https://invisiblenetwork.ai/learn/cern/3013648): Andrea Maria Ola Mejicanos · CERN - [Foundations of Statistics 4/4](https://invisiblenetwork.ai/learn/cern/3010972): Glen Cowan · CERN - [Foundations of Statistics 3/4](https://invisiblenetwork.ai/learn/cern/3010782): Glen Cowan · CERN - [Foundations of Statistics 2/4](https://invisiblenetwork.ai/learn/cern/3010752): Glen Cowan · CERN - [Foundations of Statistics 1/4](https://invisiblenetwork.ai/learn/cern/3010625): Glen Cowan · CERN - [Machine-learning in Calabi-Yau geometry](https://invisiblenetwork.ai/learn/cern/3011175): Magdalena Larfors · CERN - [Safety training processes analysis and improvements](https://invisiblenetwork.ai/learn/cern/3017911): Christel Paris · CERN - [Gender statistics in string theory](https://invisiblenetwork.ai/learn/cern/3013774): Agnese Bissi · CERN - [Towards a truly global SMEFT analysis without flavor assumptions](https://invisiblenetwork.ai/learn/cern/3006837): Tom Tong · CERN - [Two-loop RGEs from geometry](https://invisiblenetwork.ai/learn/cern/3006773): Luca Naterop · CERN - [Basic Mathematics and Units](https://invisiblenetwork.ai/learn/cern/3022871): Rende STEERENBERG · CERN - [Material from the ATLAS TOPQ-2018-04 (s-channel single top) analysis](https://invisiblenetwork.ai/learn/cern/3001956): Timothee Theveneaux-Pelzer · CERN - [Material from the ATLAS TOPQ-2020-02 (tt xsec lepton+jet) analysis](https://invisiblenetwork.ai/learn/cern/3002385): Marcel Niemeyer · CERN - [Nuclear PDFs from the nCTEQ25 global analysis and potential impact of light ion collisions at the LHC](https://invisiblenetwork.ai/learn/cern/3021464): Katrin Greve · CERN - [Digital Signal Processing II](https://invisiblenetwork.ai/learn/cern/3027015): Andrea Boccardi · CERN - [Digital Signal Processing I](https://invisiblenetwork.ai/learn/cern/3027023): Andrea Boccardi · CERN - [Tune, Chromaticity & Coupling Measurements](https://invisiblenetwork.ai/learn/cern/3027024): Rhodri Jones · CERN - [Transverse beam dynamics recap I](https://invisiblenetwork.ai/learn/cern/3027006): Hermann Schmickler · CERN - [Transverse beam dynamics recap II](https://invisiblenetwork.ai/learn/cern/3027012): Hermann Schmickler · CERN - [Adaptyst: modular architecture-agnostic performance analysis tool](https://invisiblenetwork.ai/learn/cern/3023065): Maksymilian Graczyk · CERN - [Numerical schemes for differential equations](https://invisiblenetwork.ai/learn/cern/3022773): Philippe Bourdin and Antonino Salvino Midiri · CERN - [Numerical schemes for differential equations](https://invisiblenetwork.ai/learn/cern/3022838): Philippe Bourdin · CERN - [A cost benefit analysis framework for Open Science](https://invisiblenetwork.ai/learn/cern/3021749): Gelsomina (Jessica) Catalano · CERN - [Global Collaboration Driving Open Science Impact: Insights from the RDA TIGER Landscape Analysis](https://invisiblenetwork.ai/learn/cern/3021747): Alexandra Delipalta · CERN - [Analysis of Central Diffractive Events with the CMS Precision Proton Spectrometer (PPS)](https://invisiblenetwork.ai/learn/cern/3023276): Ash Samra · CERN - [Dijet Angular Distribution Analysis in Search for New Physics](https://invisiblenetwork.ai/learn/cern/3023318): Kylene Jordan Monaghan · CERN - [Analysis of the 4-Cell Problem in the LHCb's Electromagnetic Calorimeter](https://invisiblenetwork.ai/learn/cern/3023152): Jinkyu So · CERN - [Where sample statistics matter: ATLAS improves searches for rare Higgs boson decays with the large Run 3 data set](https://invisiblenetwork.ai/learn/cern/3022687): Kun Liu · CERN - [Foundations of Statistics](https://invisiblenetwork.ai/learn/cern/3022641): Glen Cowan · CERN - [Foundations of Statistics](https://invisiblenetwork.ai/learn/cern/3023150): Glen Cowan · CERN - [Foundations of Statistics](https://invisiblenetwork.ai/learn/cern/3022578): Glen Cowan · CERN [Next page](https://invisiblenetwork.ai/learn/browse?subject=maths&page=26)