IMCI sponsors the University of Idaho as a member organization in The Carpentries training program to improve data literacy and reproducible science.
The Carpentries teaches foundational computational and data science skills to researchers worldwide. They train and certify volunteer instructors and provide curriculum in a variety of topics designed to be presented as workshops.
Past Workshops & Events
In 2019, IMCI started teaching practical programming workshops following The Carpentries lessons. Thanks to eight graduate students, postdocs who completed the required pedagogical training and 12 helpers, we ran five workshops with a total of about 150 workshop participants. For two of these workshops, we teamed up with the Idaho State University and Boise State University to provide inter-jurisdictional training opportunities.
Salvador “Chava” Castaneda
Chava is a graduate student in the Bioinformatics and Computational Biology program at the University of Idaho. He has been a carpentries instructor since 2019 and is passionate about teaching and about making the process of learning how to code less intimidating and more rewarding.
Amanda is a statistical analyst at ArcherDX, a genomics company in Boulder, CO, who has been using R extensively for statistical analysis for 8 years. She was recently certified as a Carpentries instructor and enjoys training others to use R.
Clint is a PhD Candidate in the Bioinformatics and Computation Biology (BCB) program at the University of Idaho. He is experienced in sequencing bacterial genomes and has authored a software package in Python. He enjoys helping others make connections and learn new things.
Travis is a post-doctoral researcher at University of Idaho in the department of Fish and Wildlife Sciences. Travis is interested in a broad range of ecological modelling and simulation techniques. He loves helping new learners tackle the basics of coding.
Erich is a quantitative climatologist and data scientist, who works as a postdoctoral fellow in IMCI’s geospatial modeling core initiative. Erich has a M.S. in geological sciences from Bowling Green State University and a Ph.D. in Natural Resources from the University of Idaho, with a focus on climatological analysis, machine learning, and agricultural processes. His research focuses on statistical modeling techniques to explore natural system spatiotemporal relationships, with a particular focus on climatological impacts and their varying conditional relationships to areas such as agriculture, insurance, human health, and socio-ecological feedback systems.
Breanna is a PhD student in the Bioinformatics and Computational Biology program at the University of Idaho. Breanna is grateful for a growing computational toolkit, which, for better or worse, has emboldened their knack for picking hard problems to study and making figures unnecessarily beautiful. Eager to help empower others to do and share exciting and reproducible science, Breanna has enjoyed helping with several Carpentries workshops as a certified Software Carpentry instructor, including teaching the very first IMCI-sponsored workshop alongside three fellow BCB graduate students. They are looking forward to continuing to support fellow instructors and learners.
Amanda is a PhD Candidate in the Bioinformatics and Computational Biology Program at the University of Idaho. Her research centers around characterizing the genomic basis of rapid evolution in wild populations. She became a badged Carpentries Instructor in 2019 and has taught or helped with bash, genomics, and geospatial Carpentry workshops.
James Van Leuven
James is a Research Assistant Professor in the Department of Biological Sciences and the Institute for Modeling, Collaboration, and Innovation at the University of Idaho. James uses computer programming to study microbial genome evolution and enjoys teaching students bioinformatic and computational skills.
Lihong was a postdoc at IMCI until 2020. She came to the UI from the University of Louisiana at Lafayette, where she received her PhD in Mathematics in 2017. Her research involves application of differential equations, numerical analysis, and inverse problems.