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AI3SD Video: How to detect unexpected features & physical processes in single-molecule data

AI3SD Video: How to detect unexpected features & physical processes in single-molecule data
AI3SD Video: How to detect unexpected features & physical processes in single-molecule data
This talk forms part of the ML4MC (Machine Learning for Materials and Chemicals Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Directed Assembly Network. This series ran over summer 2021 and covers topics that encompass our overlapping Network interests of AI, Machine Learning, Artificial Photosynthesis, Biomimetic Materials, Crystal Design & Engineering, Materials, Molecules, Photochemistry, Photocatalysis and Supramolecular Chemistry. This video was the sixth talk in the ML4MC series and formed part of the session "Research Talks".
AI3SD Event, Directed Assembly, Materials, Chemicals, Machine Learning, Summer School, Training
Albrecht, Tim
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Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84
Albrecht, Tim
94446f17-f189-45d4-852a-a5a5c0a6d2e3
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84

Albrecht, Tim (2021) AI3SD Video: How to detect unexpected features & physical processes in single-molecule data. Kanza, Samantha, Frey, Jeremy G. and Hooper, Victoria (eds.) Machine Learning for Materials & Chemicals Seminar Series 2021, , Southampton, United Kingdom. 06 Jul - 24 Aug 2021. (doi:10.5258/SOTON/P0132).

Record type: Conference or Workshop Item (Other)

Abstract

This talk forms part of the ML4MC (Machine Learning for Materials and Chemicals Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Directed Assembly Network. This series ran over summer 2021 and covers topics that encompass our overlapping Network interests of AI, Machine Learning, Artificial Photosynthesis, Biomimetic Materials, Crystal Design & Engineering, Materials, Molecules, Photochemistry, Photocatalysis and Supramolecular Chemistry. This video was the sixth talk in the ML4MC series and formed part of the session "Research Talks".

Video
Ml4MC-TimAlbrecht-270721 - Version of Record
Available under License Creative Commons Attribution.
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More information

Published date: 27 July 2021
Additional Information: Tim studied Chemistry at the University of Essen in Germany from 1995-2000. Following brief research visits at the European Joint Research Centre in Ispra in Italy and the University of California at Berkeley, Tim graduated with a Diploma in Chemistry (equivalent to a Masters degree) in early 2000. After graduating, Tim joined Peter Hildebrandt’s group at the Max-Planck Institute for Radiation Chemistry (now Bioinorganic Chemistry) in 2000. Tim worked on charge transfer processes in natural and artificial heme proteins on metal surfaces using SER(R)S, single-crystal electrochemistry and electrochemical STM (in Jens Ulstrup’s group at the Technical Institute of Denmark (DTU). He obtained his PhD from the Technical University (TU) of Berlin in 2003 and afterwards returned to Ulstrup’s group as a postdoctoral fellow. In 2006, he moved to London to take up a lecturer position in Interfacial and Analytical Sciences in the Chemistry Department at Imperial College, where he was made Senior Lecturer in 2011 and then Reader in 2014. In 2017, Tim joined the faculty in the School of Chemistry at Birmingham University as Chair of Physical Chemistry and has been the School of Chemistry’s Director of Research since 2018. He is the coordinator of the School’s Interest Group “Data and Machine Intelligence”.
Venue - Dates: Machine Learning for Materials & Chemicals Seminar Series 2021, , Southampton, United Kingdom, 2021-07-06 - 2021-08-24
Keywords: AI3SD Event, Directed Assembly, Materials, Chemicals, Machine Learning, Summer School, Training

Identifiers

Local EPrints ID: 450670
URI: http://eprints.soton.ac.uk/id/eprint/450670
PURE UUID: 0fa1db6e-fd6e-4215-9ac8-a1cbb1500898
ORCID for Samantha Kanza: ORCID iD orcid.org/0000-0002-4831-9489
ORCID for Jeremy G. Frey: ORCID iD orcid.org/0000-0003-0842-4302

Catalogue record

Date deposited: 05 Aug 2021 16:35
Last modified: 21 Aug 2021 01:56

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Contributors

Author: Tim Albrecht
Editor: Samantha Kanza ORCID iD
Editor: Jeremy G. Frey ORCID iD
Editor: Victoria Hooper

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