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@DannyVanpoucke
Danny Vanpoucke DannyVanpoucke
Computational Materials Researcher exploring the interface between simulation and reality for materials of the future.

Prof. @HasseltUniversity Delocalized between physics, chemistry and computation.

@camlab-ethz
Computational and Applied Mathematics Laboratory @ ETH Zurich camlab-ethz
We are part of the Seminar for Applied Mathematics at the Department of Mathematics.

Switzerland

@Materials-Consortia
Open Databases Integration for Materials Design Materials-Consortia
The Open Databases Integration for Materials Design (OPTIMADE) makes the materials databases interoperational by developing a common REST API.
@chiang-yuan
Yuan (Cyrus) Chiang chiang-yuan
PhD student in @astagroup at UC Berkeley and LBNL

UC Berkeley, Lawrence Berkeley National Laboratory Berkeley

@matlantis-pfcc
Matlantis matlantis-pfcc
Official account of the universal atomistic simulator "Matlantis"
@perturbo-code
Perturbo perturbo-code
Perturbo is a software platform to compute from first principles the scattering processes among electrons, phonons, defects, photons, and excitons in materials.
@unitaryfund
Unitary Fund unitaryfund
Unitary Fund is a non-profit working to create a quantum technology ecosystem that benefits the most people.
@dsambit
Sambit Das dsambit
Assistant Research Scientist. One of the lead developers of DFT-FE.

University of Michigan

@deepmodeling
DeepModeling deepmodeling
Define the future of scientific computing together
@NuclearTalent
Nuclear Talent NuclearTalent
Repository for Nuclear TALENT (Training in Advanced Low-Energy Nuclear Theory)
@yuanqidu
y6q9 yuanqidu
CS PhD student at Cornell, working on Geometric Deep Learning, Deep Generative Model, and AI for Science

Cornell University

@m-stack-org
M-Stack m-stack-org
Modelling of Materials and Molecules with Machine Learning
@jwa7
Joseph W. Abbott jwa7
PhD candidate @lab-cosmo, EPFL in ML for atomistic simulations. Currently machine learning real-space densities of electronic states.

Lab COSMO, EPFL Lausanne

@AC-BO-Hackathon
AC BO Hackathon AC-BO-Hackathon
Organization for orchestrating the Bayesian Optimization Hackathon for Chemistry and Materials sponsored by the Acceleration Consortium and Merck KGaA.

Canada

@carpentries
The Carpentries carpentries
The Carpentries teaches foundational coding, and data science skills to researchers worldwide.
@pyOpenSci
pyOpenSci pyOpenSci
We build diverse community around the tools that drive open science through open peer review, mentorship and training.
@lfai
LF AI & Data Foundation lfai
LF AI & Data is an umbrella foundation under the Linux Foundation that supports and sustains open source innovation in AI, ML, DL and Data.

San Francisco, California

@PythonFZ
Fabian Zills PythonFZ
Ph.D. Student in Computational Physics

University of Stuttgart Germany

@exalearn
ExaLearn exalearn
ECP Exascale Machine Learning Project
@jameskermode
James Kermode jameskermode

University of Warwick Coventry, UK

@markus1978
Markus Scheidgen markus1978

Humboldt-Universität zu Berlin Berlin, Germany

@nomad-coe
NOMAD CoE and Laboratory nomad-coe
This organisation of the Novel Materials Discovery (NOMAD) Center of Excellence and Laboratory develops FAIR tools for materials-science data.
@DLR-SC
DLR Institute for Software Technology DLR-SC
German Aerospace Center (DLR)

Cologne, Berlin, Braunschweig, Oberpfaffenhofen, Bremen

@sdruskat
Stephan Druskat sdruskat
Software engineering researcher and PhD candidate @DLR-SC

German Aerospace Center (DLR) Berlin

@AccelerationConsortium
Acceleration Consortium AccelerationConsortium
A global community accelerating the design and discovery of wide range of new materials, from renewable energy to drugs.

Canada

@sparks-baird
Sparks/Baird Materials Informatics sparks-baird
Sterling Baird and Taylor Sparks Materials Informatics Projects

United States of America

@janosh
Janosh Riebesell janosh
Integrating ML foundation models for chemistry with robotic labs

Radical AI New York

@zotroneneis
zotroneneis zotroneneis

inovex Bonn, Germany

@probml
Probabilistic machine learning probml
Material to accompany my book series "Probabilistic Machine Learning" (Software, Data, Exercises, Figures, etc)
@lamalab-org
Laboratory for AI for Materials lamalab-org
Independent research group led by Kevin Maik Jablonka