Thomas Struble

Organic chemist turned to the dark side of machine learning and informatics.

[Thomas Struble @thomasstruble]

Going to #ACSFall2024 and interested in prospective applications of machine learning in chemistry? Come by on Monday to the mile high ballroom to see a fanstistic lineup of leaders in the field including @chemchristensen, @reisman Brent Koscher, @teodorolaino , and @marwinsegler

[Thomas Struble @thomasstruble]

@IR_SP8 @Chemjobber This is so cool to see!

[kangway chuang @kangway]

We have an awesome postdoc opportunity in my lab @PrescientDesign as part of @genentech Research and Early Development, co-advised by James @crwfrd_SF in Discovery Chemistry. Come work with us on the next generation of ML approaches for chemical discovery! https://t.co/AXCZgwzckN

[Thomas Struble @thomasstruble]

@iwatobipen When you figure this out tell us all the secrets of how to do it successfully 😅

[Thomas Struble @thomasstruble]

Amazing workshop, thanks @tiwarylab for all the coordination and getting a stellar lineup of speakers! Lots to be done in ML+Chemistry and the discussions were very enlightening

[Gabe Gomes @gabepgomes]

We @gpggrp will have an opening for an @NSF_CCAS postdoc soon. The ideal candidate must have experience and/or interest in at least some of the following: • computational/physical organic chemistry; • ML & evolutionary computing; • (bio)catalysis/(bio)organic materials.

[Thomas Struble @thomasstruble]

@CarlNising Thing are definitely looking up and it is good to start being more proactive about it. These types of editorials are great to spread more awareness of the problems.

[Thomas Struble @thomasstruble]

Mostly agree. The comparison to other realms is not good though. Chemistry data is expensive which means we have to find intelligent ways to use the data not generate data that fits the algorithm. Principled data generation is important but won’t solve the problem.

[Thomas Struble @thomasstruble]

@matteo_aldeghi @BayerPharma Congrats!!

[Thomas Struble @thomasstruble]

Awesome work Oliver!!

[Oliver Schilter @OSchilter]

Explore our latest paper on designing catalysts using deep generative models and computational data. Discover how an RNN-VAE can generate new catalyst candidates for the Suzuki coupling. https://t.co/qaTfzq2JXb @IBMResearch @SchwallerGroup @acvaucher @pschwllr @teodorolaino

[Thomas Struble @thomasstruble]

@SuperScienceGrl People live stream coding on twitch, why not chemistry 😅

[Pushkar Ghanekar @mepgg]

Hiring for a post-doctoral position in reaction informatics. In this role, you will develop new ways that allow novel chemical transformations to unlock new chemical spaces. Happy to help with questions!

https://t.co/g4dxm4pSud

#cheminformatics #hiring #postdoc #drugdiscovery

[Thomas Struble @thomasstruble]

This is a really important question to have answered for yourself before applying and interviewing. I can’t tell you how many candidates I’ve screened that simply say I just want a job. While that is valid, the jobs usually go to someone that has a passion for the type of work.

[Academic Exit @academic_exit]

PhDs working outside of academia: how did you know what type of job you wanted to apply for?

Inquiring minds (of PhDs still in academe) want to know.

[Thomas Struble @thomasstruble]

@rguha For one off data analyst then cartridge is probably better IMO. For delivering to chemists we actually have other even faster option which is not cost effective from the compute side but very effective saving min-hrs of >300 chemists time weekly

[Thomas Struble @thomasstruble]

@rguha Complicated question! The value for us comes at large scale repeated tasks that can and should be automated 1) freeing scientists time is cost effective and 2) dynamic horizontal scaling only pays for compute for a short time 3) shared responsibility with IT is easier

[Thomas Struble @thomasstruble]

@rguha Doing some basic filtering at the db query level if you can, then using spark to distribute the SSS or sim search is the best I got so far when cartridges aren’t available, then returning only molecules with match or sim threshold

[Thomas Struble @thomasstruble]

@rguha We built a lot of MLOps infrastructure on databricks but our tables are all in AWS (redshift or Postgres) so would just use the cartridges there. Not easy with redshift which is probably similar to the tables on databricks itself.

[JCIM & JCTC Journals @JCIM_JCTC]

Matcher: An Open-Source Application for Translating Large Structure/Property Data Sets into Insights for #DrugDesign #cheminformatics
https://t.co/Q3b05Do0an
Vol63 Issue7 #JCIM #Application_Notes

[Thomas Struble @thomasstruble]

@KRHornberger Happy to team up on best practices from the predictive side as well for anyone that has question on any of these topics in regard to QSAR modeling. Why memorize EVERY rule for EVERY endpoint when you can automate some of the pattern recognition