Callouts

Learn about Graduate School – Free Events from Purdue Engineering

I am excited to let you know about two upcoming (FREE!) opportunities to learn more about graduate school and paid summer research at Purdue Engineering!


1. Purdue Engineering GradTrack ScholarsApplication Deadline May 14, 2021

If you are an underrepresented student in engineering and interested in learning more about graduate school, then this online mentoring cohort is for you!

GradTrack Details: Monthly online meetings (1.5 hrs each) from August 2021 – April 2022 (see dates on website)

  • Engage in presentations and conversations that demystify graduate school, summer research programs, and the application process.
  • Learn from mentors who are current Purdue Engineering BIPOC graduate students.
  • Be part of a supportive and limited cohort.
  • Finish the program with completed documents for a competitive graduate school or summer research application.

Learn more and apply by May 14th at:  https://engineering.purdue.edu/Engr/Academics/Graduate/gradtrack

2. Purdue Engineering ShowcaseJoin our mailing list here.

Save the date for October 3-4, 2021. Meet Purdue Engineering Graduate Programs and Faculty, and learn about both graduate research and summer undergraduate research programs at Purdue. Free, online, and interactive. Sign up for our mailing list to receive event updates and be notified when registration opens.

Learn more at: https://engineering.purdue.edu/Engr/Academics/Graduate/graduate-showcase

If you have questions, please email any member of our team at engrgrad@purdue.edu

Callouts

Hands-on, free, workshop on machine learning May 12th and May 19th, 2021 at 1:30 PM EDT – registration open (limited seats)

nanoHUB is excited to announce the nest two workshops in the Spring 2021 session of our Hands-on Data Science and Machine Learning Training Series. 

Series information. Our series is aimed at active researchers and educators and designed to introduce practical skills with online, hands-on activities participants will be able to incorporate in their work. Hands-on activities will use nanoHUB cloud computing resources, no need to download or install any software. All you need is an internet connection and a browser. After the training sessions, you will be able to continue using nanoHUB for research or education.
Registration links and material for prior workshops can be found at the workshop webpage: https://nanohub.org/groups/ml/handsontraining 

Register soon as seats are limited. 

Date: May 12th 2021,  1:30 PM – 2:30 PM EST
Title: An Introduction to Machine Learning for Materials Science: A Basic Workflow for Predicting Materials Properties
Speaker:
Benjamin Afflerbach, University of Wisconsin-Madison

Register here (limited seats): https://nanohub.org/groups/ml/handsontraining 

Abstract.
This workshop will introduce core concepts of machine learning through the lens of a basic workflow to predict material bandgaps from material compositions. As we progress through this workflow, we’ll highlight key steps, challenges that can come up with materials data, and potential solutions to these challenges. The core workflow we’ll introduce includes: Data Cleaning, Feature Generation, Feature Engineering, Establishing Model Assessment, Training a Default Model, Hyperparameter Optimization, and Making Predictions. By the end of the workshop I hope that you’ll have a better understanding of these core concepts, and how they can all fit together. If you want to preview the materials ahead of time you can find them on nanoHUB here: https://nanohub.org/tools/intromllab.

Date:  May 19th 2021,  1:30 PM – 2:30 PM EST
Title: Automating Development and Evaluation of Machine Learning Models for Materials Property Prediction
Speaker:
Ryan Jacobs, University of Wisconsin-Madison

Register here (limited seats): https://nanohub.org/groups/ml/handsontraining 

Abstract. This tutorial contains an introduction to the use of the Materials Simulation Toolkit for Machine Learning (MAST-ML), a python package designed to broaden and accelerate the use of machine learning and data science methods for materials property prediction. Through hands-on activities, we will use MAST-ML to (1) import materials datasets from online databases and clean and examine our input data, (2) conduct feature engineering analysis, including generation, preprocessing, and selection of features, (3) construct, evaluate and compare the performance of different model types and data splitting techniques, and (4) conduct a preliminary assessment of model error analysis and uncertainty quantification (UQ).

MAST-ML code: https://github.com/uw-cmg/MAST-ML
Publication: https://doi.org/10.1016/j.commatsci.2020.109544
MAST-ML tutorials: https://github.com/uw-cmg/MAST-ML/tree/master/examples

Callouts, Scholarships

Calling all Rising Seniors Considering Grad School

Thinking about grad school for the future? As you enter your senior year, I want to make you aware of the National Science Foundation (NSF) Graduate Research Fellowship, which provides a $34,000 stipend and tuition coverage each year for three years. It’s the best way to fund your masters or PhD! Students in a variety of STEM and social science fields are allowed to apply as senior undergraduates and undergraduate applicants have a greater chance of winning than current graduate students.

The Fellowship Office at Purdue is here to advise you on your NSF application writings. We’re here to help you get started over the summer with as little stress as possible!  

To start preparing your application, attend the upcoming webinar info sessions, which are offered as three webinars in two different sequences with the same content. Pick whichever time suites your schedule.  

May webinars during Wednesday lunch time: 

June webinars on Tuesday evenings: 

The NSF Fellowship is open to US citizens and permanent residents, but everyone is welcome to attend the webinars because the information can be used to apply for other graduate fellowships.