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CABTalk S1E8: Chloe Hsu (UC Berkeley) & Dan Crowther (Exscientia)

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Manage episode 290867694 series 2917016
Content provided by Fane Mensah and Synthace and Fane Mensah. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Fane Mensah and Synthace and Fane Mensah or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

It's Industry vs Academia on the podcast this month! We’ve got Exscientia’s Dan Crowther and PhD Student Chloe Hsu discussing Machine Learning and Drug Discovery – don’t miss out on our exciting chat about what makes a good drug target and how do you tackle reproducibility issues in software.

Chloe and Dan also chat about the differences between academia and industry, and how they need each other to work. Both our guests get to ask each other a burning question - great insight into how the other side works!

  continue reading

30 episodes

Artwork
iconShare
 
Manage episode 290867694 series 2917016
Content provided by Fane Mensah and Synthace and Fane Mensah. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Fane Mensah and Synthace and Fane Mensah or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

It's Industry vs Academia on the podcast this month! We’ve got Exscientia’s Dan Crowther and PhD Student Chloe Hsu discussing Machine Learning and Drug Discovery – don’t miss out on our exciting chat about what makes a good drug target and how do you tackle reproducibility issues in software.

Chloe and Dan also chat about the differences between academia and industry, and how they need each other to work. Both our guests get to ask each other a burning question - great insight into how the other side works!

  continue reading

30 episodes

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