Hub Updates is the UW-Madison data science community's resource for news, trainings & workshops, and professional opportunities in data science.
If you have feedback on the new format or suggestions for other news, events, and opportunities to include, send us an email at newsletter@datascience.wisc.edu.
Have questions about anything data science-related? Come see us at Coding Meetup on Tuesdays and Thursdays from 2:30-4:30 p.m. CT. To join Coding Meetup, join data-science-hubgroup.slack.com.
November 30, 2022
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Posit is a real word that means to put forth an idea for discussion. Data scientists spend much of their day positing claims that they then evaluate with data. When considering a new name for the company, the team wanted something that reflects both the work our community engages in (testing hypotheses!) as well as the scientific aspiration to build ever-greater levels of knowledge and understanding.
RStudio decided to change their name to Posit because their charter defines their mission as the creation of free and open source software for data science, scientific research, and technical communication. This mission intentionally goes beyond “R for Data Science”— they hope to take the approach that’s succeeded with R and apply it more broadly. Posit wants to build a company that is around in 100 years time and continues to have a positive impact on science and technical communication. For any questions, visit the updated blog post, which contains the most up-to-date Posit FAQs.
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Upcoming Trainings & Workshops
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Fall 2022 Mini Workshop Series, Data Science Hub
December 14, 9:00 a.m. to 12:30 p.m. CT, Virtual, The Data Science Hub will be hosting a series of mini workshops starting this fall. The last workshop will be an introductory lesson to Julia. Each workshop can be registered for separately and has their own pre-requisites. To view the workshop itineraries and register, visit the Fall 2022 Mini Workshop Series website.
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Upcoming Seminars & Events
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SILO Seminar Series
SILO is about breaking down the systems, information, leaning, and optimization of research created by academic department boundaries. Recent advances in information science are allowing scientists and researchers to sense, process and share data in ways and scales previously impossible. These developments have the potential to benefit work happening in a wide range of disciplines. SILO’s purpose is to help realize such potential by providing the time and space for researchers to present and interact to find common threads. SILO seminars take place at 12:30 p.m. every Wednesday. Visit the SILO webpage for information about their upcoming talks.
ML+Coffee Social
December 7, 9:00 a.m. to 11:00 a.m., Discovery Building, Hosted by the Machine Learning Community, this monthly social event is intended to help machine learning practitioners across campus connect with one another, discuss and work on projects together, and most importantly — enjoy some free refreshments. Laptops are encouraged. Those who wish to attend are encouraged to bring their laptops and any questions related to their ML projects. To receive an invite containing the room location, fill out the ML+Coffee registration form.
Genomics Seminar Series, Center for Genomic Science Innovation
December 1, 1:30p.m., Online, The Center for Genomic Science Innovation will be hosting speaker Dana Pe'er on Having Fun with Single Cell Biology: Beyond Clusters and UMAPs. Visit the Zoom link at the respective time to join this seminar and listen to Dana Pe'er discuss her research at the Pe'er Lab. There will be an extended Q+A at the end of the discussion.
ML+X Forum: Bias and Fairness, ML Community
December 6, 12:00 p.m. to 1:00 pm., In-person, Bias is a somewhat overloaded term in the field of machine learning that often needs to be defined within a specific context. Join the ML Community to learn about some of the different forms of bias (e.g., data bias vs model bias) that can influence a model's decision making process (for better or for worse), as well as some tips on how to ensure that your model behaves fairly. Visit the ML+X Forum event page for more information about its presenters and the location.
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GPUs in Google Collab Workshop, dotData
November 30, 6:00 p.m., Computer Sciences 1240, dotData will be hosting an interactive workshop led by their president, Gautam. Laptops will be required and food will be provided. Sign up for the dotData newsletter for updates about upcoming events.
Student Mentor
Seeking tutor on Android Mobile Dev to help fill knowledge gaps and gain deeper understanding. The student must be proficient in Kotlin and Android architectural components, especially LiveData and Flow. The successful candidate will Ideally meet once a week, for up to 5 hours at a time, at a rate of $20/hour, beginning to mid January 2023 (flexible). Contact catherine@catalexandra.dev to express interest or for more information.
Math 888: Topics in Math Data Science, UW-Madison Spring Course
Taught by Professor Qin Lin, Math 888 will focus on the itnterplay between data and differential equations (DEs). This course plans to (1) Investigate a class of inverse problems. This amounts to inferring unknown parameters in equations. Involved techniques include PDE-constrained optimization, adjoint method, and Bayesian sampling, and experimental design and (2) Investigate the optimal transport guided data science tools, including ensemble Bayesian methods, Kalman methods/filters, and mean-field neural networks. Visit the Course Search & Enroll app in the student center to enroll.
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Professional Opportunities
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On Campus
Postdoctoral Associates and PhD Candidates, Steel Systems Innovation Research Lab
Join a dynamic and interdisciplinary project dealing with monitoring, modeling, and visualization of damage. The project includes distributed fiber optic sensing, e.g., distributed acoustic sensing (DAS), distributed strain sensing (DSS), and distributed temperature sensing (DTS), and campaigns to monitor structural damage and behavior. Fiber optic sensing campaigns will focus on both new and historic structures in locations around the world. Structural behavior will be assessed via advanced Finite Element (FE) modeling to understand deterioration as a function of changing loading conditions. Mixed reality visualization will aid in damage assessment, remote sensing, and FE model integration. Candidates will work closely as a team involving 3 Postdoctoral Scholars and 4 PhD students with PI Hannah Blum and PI Jesse Hampton, along with skilled augmented reality software engineers. For more information and to apply, view the position description document.
Data Scientist, Data Science Institute
The Data Science Institute (DSI) is looking for multiple data scientists to join our growing team. Their mission is to perform cutting-edge research in the fundamentals of data science, to catalyze the translation of this research into practice, and to advance scientific discovery in collaboration with researchers across campus and beyond. DSI's vision is to lead a vibrant, innovative, inclusive, and collaborative data science research community and advance the social good through a coherent research agenda backed by resources, space, and data science expertise. For more information and to apply, visit the Data Scientist position description.
Data Scientist, Midwest Center of Excellence for Vector-Borne Disease
The Data Scientist will collaborate closely with members of the Midwest Center of Excellence for Vector-Borne Disease (MCEVBD), working with Susan Paskewitz (CALS - Department of Entomology) and Lyric Bartholomay (SVM - Department of Pathobiological Sciences). The Data Scientist will contribute to multiple research projects that include: 1) evaluating currently available methods for reduction of host-seeking blacklegged ticks or West Nile virus vectors, 2) laboratory, semi-field, and field trials evaluating new products and delivery mechanisms for tick or mosquito control, 3) evaluating impacts of public health education on vector bite prevention. For more information and to apply, visit the Data Scientist position description.
Off Campus
Data Science Informationist, University of Colorado-Boulder
The Data Science Informationist collaborates with and lends support to research departments, laboratories, and individual scientists within the University of Colorado Anschutz Medical Campus (CU Anschutz) in matters relating to data management, bioinformatics, and scientific computing. As a member of the Education and Research department, the Data Science Informationist also actively participates in instruction, reference, consultation, searching, and liaison services. For more information and to apply, visit the Data Science Informationist position description.
Research Data Librarian, Tufts University
The Research Data Librarian supports a range of services related to accessing, using, and managing quantitative and other types of scientific data. This position works with student, faculty, and staff users and producers of data, and helps to identify, develop, implement, and assess data services to meet the needs of the Tufts community. The Research Data Librarian will: Provide outreach, consultation, and instruction in various modalities on topics, foster relationships with departments, research institutes or centers, and laboratories in order to maximize support across campus, and actively contribute to and promotes data curation services in Tufts repositories. For more information and to apply, visit the Research Data Librarian position description.
Assistant Professor Electrical and Computer Engineering, University at Albany
The College of Engineering and Applied Sciences of the University at Albany seeks applicants for two tenure-track Assistant/Associate Professors, beginning Fall 2023 for its Electrical and Computer Engineering Department. The successful candidate is expected to develop an externally funded research program in electrical and computer engineering. In addition, the applicant will be responsible for teaching courses at the undergraduate and graduate levels, including both fundamental lower-division courses and upper-division and graduate courses related to their area of expertise. Teaching assignments will be determined by the candidate's expertise and the needs of the Department. For more information and to apply, visit the Assistant Professor position description.
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