We, Dr. Omar Valsson and PhD candidate Ignacio Migliaro from University of North Texas Chemistry, are going to organize a didactic seminar series where once a month we will meet for around 1.5-2 hours and share different methodologies in machine learning applied to areas in both chemistry and material science. Our goal is for people to present and teach different ML methods and how they can be implement in these different fields.

Everyone from UNT Chemistry, Physics, Materials Science, and also others at UNT, will be welcome to participate, both undergraduate students and graduate students.

If you are interested to participate, please contact Dr. Omar Valsson [email protected] and Ignacio Migliaro [email protected].

The planned format of the seminars is that we will start with around 45-60 minutes of presenting background and theory and sharing articles, followed by around 45-60 minutes of immersive learning where the presenter will teach the audience how to implement the presented ML methods with hands-on tutorials.

As of now we plan on covering the following topics:

• AlphaFold (protein structure prediction using deep learning)
• Tensorflow/Pytorch (fundamentals)
• High Throughput Screening (both for materials and molecules)
• Cheminformatics (SMILES, SELFIES, fingerprints, etc..)
• Materials and molecule discovery (Materials Project, CCD)

Participants are encouraged to suggest and contribute with topics they are interested in.

We plan on starting the seminar series in the early Spring 2023 semester. The exact schedule for seminar series will be decided later.

In the first seminar, Dr. Omar Valsson will give a presentation on AlphaFold and how to use it in practise.

Please get in contact if you have any questions or comments.

Dr. Omar Valsson [email protected] and Ignacio Migliaro [email protected]