In the August 21, 2019 update:
- The Carpentries
- Upcoming Campus Events
- Upcoming Training and Workshops
- Campus Opportunities and Groups
- External Opportunities
- Featured Course Offerings for Fall 2019
- unsure which campus data and computing resources you need for your research?
- interested in making connections and starting new collaborations with data scientists and other researchers on campus?
- looking for training in data and computing skills?
The Data Science Hub can help! Send an email to the Data Science facilitator (firstname.lastname@example.org) or come by Hub Central in the Discovery Building during office hours (Th 3:00-5:00 PM). Sarah will also be at Open Coding Lab in Steenbock Library (T 2:30-4:30 PM). Check calendar for latest details and updates.
The University of Wisconsin – Madison has a long standing relationship with The Carpentries, a global organization of researchers who volunteer their time and effort to create workshops that teach software engineering and data analysis skills to other researchers. The Data Science Hub carries on the tradition of hosting these workshops on the UW-Madison campus. More information about the workshops can be found on the Training page of the Data Science Hub website.
Upcoming Campus Events (Calendar View)
The Wisconsin Association for Computing Machinery – Women in Computing (WACM-W) meets every month on the first Tuesday of each month.
Sept 3, 12:15pm-1:15pm, Computer Sciences 2310.
Center for Demography of Health and Aging (CDHA) Training Seminar: 2:00pm-3:15pm, 8417 Sewell Social Science Building
Sept 4, Reproducible Research, Lars Vilhuber (Cornell Economics)
Statistics Seminar: 4:00pm, 140 Bardeen
Sept 4, TBA, Joshua Cape
Applied and Computational Mathematics Seminar (ACMS): 2:25pm, 901 Van Vleck Hall
Sept 6, TBA, Leonardo Andrés Zepeda Núñez
Upcoming Training and Workshops
R workshops for Researchers
UW-Madison libraries are offering R programming Workshops on R programming for researchers. The content will cover useful skills for anyone working with tabular data. Later sessions go beyond the Data Carpentry Lessons to cover how to use git version control within R Studio and writing reproducible reports using RMarkdown. Registration is by workshop, not for the entire series. A full list of workshops and registration information can be found here.
R/RStudio for Independent Learners
This is a brief introduction to R and RStudio designed for those who want to learn R and RStudio but only need help getting started. This covers enough R and RStudio to prepare you the Tidyverse for Independent Learners course. The course date is 9/3 (9:00-10:30) and will be held in Sewell Social Sciences Building. If you are interested, you can register here.
Tidyverse for Independent Learners
This is a brief introduction designed for those who want to learn the tidyverse but only need help getting started. The course date is 9/3 (11:00-12:30) and will be held in Sewell Social Sciences Building. If you are interested, you can register here.
Data Wrangling in R
“Data Wrangling” is the process of preparing data for analysis, which includes importing, cleaning, recoding, restructuring, combining, and anything else data needs before it can be analyzed. This course teaches wrangling skills using the tools of the tidyverse. The course dates are 9/4, 9/9, 9/11, 9/16, 9/18, 9/23, 9/25, 9/30, 10/2, and 10/7 (1:00 – 3:00). Note that this class is a series and you should plan on attending all of the sessions. If you are interested, you can register here.
Introduction to Stata
In this class you’ll learn the basics of how Stata works and how to use it. This class (or comparable experience) is a prerequisite for the rest of SSCC’s Stata training. It will also prepare you to excel in classes that use Stata, like Sociology 361 or Economics 410. We suggest new graduate students consider taking this class before or during their first semester. The course will be taught 9/3 from 1:00-3:00 in the Sewell Social Sciences Building. If you are interested, you can register here.
Data Wrangling in Stata
“Data Wrangling” is the process of preparing data for analysis, which includes importing, cleaning, recoding, restructuring, combining, and anything else data needs before it can be analyzed. In this class you’ll learn how to wrangle data using Stata. The course dates are 9/11, 9/16, 9/18, 9/23, 9/25, 9/30, and 10/2 (9:00 – 12:30). Note that this class is a series and you should plan on attending all of the sessions. If you are interested, you can register here.
UW Extended Campus Coding Bootcamp
The digital revolution has transformed virtually every area of human activity—and you can become part of it as a web development professional. UW Extended Campus Coding Boot Camp is a live, online Full Stack Flex course with a part-time schedule that gives you the knowledge and skills to build dynamic end-to-end web applications and become a full stack web developer in 24 weeks. Designed to fit into the lives of busy adults and working professionals, the program features convenient online classes in real-time, with evening and weekend sessions. We pair live classes with in-depth, curated resources to reinforce knowledge and supplement those days you can’t make the live session. You can learn more here.
Campus Opportunities and Groups
Senior Data Scientist Position
The Department of Medicine is looking for a Senior Data Scientist to join their growing, multi-disciplinary clinical research data science and machine learning team. The Data Scientist will support the lab by conducting data analysis that centers on developing algorithms for modeling clinical patient data as well as statistical analyses of qualitative and quantitative data. This position will work under the Direction of Dr. Matthew Churpek, whose research focuses on using electronic health record data combined with epidemiology, biostatistics and machine learning methods to improve the care of hospitalized patients. The Senior Data Scientist will be responsible for oversight of data cleaning and management, the development and maintenance of clinical research databases, and the development and execution of complex data analyses and machine learning modeling projects. Applications close August 30.
Data Wonks Community of Practice
The Data Wonks (formerly known as the Ad Hoc Query Writers CoP) is a UW-Madison Community of Practice for individuals who work with campus data and the provided tools. The next meeting of the Data Wonks is 9/11 from 12:00-1:00 in Bascom Hall. This is one in a series of semi-monthly meetings. The topic this month is Writing Queries in Toad Data Point and is presented by Nick Sigmund, Policy and Planning Analyst.
Machine Learning for Medical Imaging: Pilot Research Grants for Collaborative Projects
The purpose of this program is to foster interdisciplinary collaboration between machine learning (ML) experts and medical imaging clinicians and researchers at the University of Wisconsin, in order to develop and apply state-of-the-art ML solutions to challenging problems in medical imaging. This includes developing new ML methods for medical imaging applications, and exploring new imaging applications of state-of-the-art ML methods. Potential applicants are encouraged to contact Diego Hernando or Varun Jog for additional details. Pilot awards are $50,000 maximum in direct costs for 12 months of support. Mandatory Letter of Intent Receipt Date: August 23, 2019.
Workshop on Distributed Estimation and Control in Networked Systems (NECSYS)
NECSYS is a two-day workshop consisting of a single-track set of talks and a couple poster sessions. The workshop covers a wide range of topics of interest to engineers, computer scientists, and optimizers, including: Multi-agent systems, Control under communication constraints, Consensus and gossip algorithms, Decentralized and cooperative control/estimation, Distributed optimization and MPC, Cyber security in networked control systems, Event-triggered and self-triggered control, Wireless sensing and control systems, Graph-based methods for networked systems, Cooperation in the presence of adversaries, and Networked games. For more information, check out the NECSYS website.
National Science Policy Network (NSPN) Symposium
Catalysts for Science Policy is hosting the NSPN’s annual symposium here in Madison, WI on November 1-3, 2019. This year’s theme is “Leveraging Science and Technology to Benefit Marginalized Populations.” The symposium features speakers, workshops, and 300+ attendees. Information about the symposium can be found here. Early bird registration ends August 30 and individuals who qualify to become NSPN members can receive a 50% discount.
Actuarial Internship for Undergraduates, CVS Health
CVS Health is the nation’s premier health innovation company helping people on their path to better health. They are building a new health care model that is easier to use, less expensive, and puts the consumer at the center of their care. The Corporate Internship Program is a nationally recognized experience; it is also a great way to gain confidence, sharpen your skills, and make a difference. You can learn more here.
Big Data Neuroscience Workshop
This workshop will continue work on the development of common practices and standardization to make it easier for neuroscience researchers to annotate and process data; to share data, tools and protocols, and to work with distributed high-performance computing environments. The workshop will bring together members of the Midwest, national, and the global neuroscience research community to promote data reuse, aggregation, result validation and new discoveries in neuroscience. Program and registration details can be found here.
Deep Learning: Mathematical Foundations and Applications to Information Science
The IEEE Journal on Selected Areas in Information Theory (JSAIT) seeks high quality technical papers on all aspects of Information Theory and its applications. JSAIT is a multi-disciplinary journal of special issues focusing on the intersections of information theory with fields such as machine learning, statistics, genomics, neuroscience, theoretical computer science, and physics. This special issue will focus on the mathematical foundations of deep learning as well as applications across information science. Prospective authors are invited to submit original manuscripts on topics within this broad scope including, but not limited to: Information theoretic methods for deep learning, robustness for training and inference, understanding generalization in over-parametrized models, efficient and compressed model representations, deep generative models and inverse problems, large-scale efficient training of large models, non-convex optimization in deep learning, and deep learning for source and channel coding. For details and templates, please refer to the IEEE Journal on Selected Areas in Information Theory Author Information webpage. All papers should be submitted through Scholar One by October 1, 2019.
Data Science Forum 2019
September 17 – 18, Cornell University, Ithaca, NY
The Data Science Forum is an opportunity for institutions of higher education to share ideas, perspectives, and solutions designed to extract value from our institutional data. Broad topics will include: data and infrastructure strategy; hiring the “right” expertise; big data, machine learning, and statistical modeling; privacy and legal concerns; and pitfalls and success stories. They would like to have as many institutions as possible participate in these discussions. To that end, they ask that you send at most two representatives from your institution. If in addition to your two representatives you have a speaker well suited to one of the topics listed on the registration form, please contact Cecilia Earls for special consideration.
Featured Course Offerings for Fall 2019
Computational Network Biology Course – This course surveys the current literature on computational, graph-theoretic approaches that use network algorithms for biological modeling, analysis, interpretation and discovery. The material covered in this class will come from published literature, review articles, and selected book chapters. Students will participate in discussions of papers and gain hands-on experience in network biology by implementing class projects. This class should be of interest to students from multiple disciplines including computer science, engineering, math, statistics, microbiology, biochemistry and genetics. Learn more here.
Forensic Science and Law Course – Taught by Professors Jo Handelsman (Plant Pathology) and Kieth Findley (Law), this is the first course at the University of Wisconsin—and among the first in the nation—to bring together law students and graduate students in STEM to examine law and forensic science together. The course will focus on the legal system and processes, the fundamentals of science and the challenges confronting the forensic disciplines, and close scrutiny of many of the dominant forensic techniques used today. Find PL PATH 875-005 (66958) in the UW course guide. The class meets 4:10-5:30 pm on Tuesdays and Thursdays in the Discovery Building.
If you have a course you would like us to feature, please send us an email at email@example.com.
Check calendar for latest details and updates for all listed events. If you have a relevant event or group you’d like to see included in next month’s newsletter. Please send us an email at firstname.lastname@example.org.