080719 Update

UPDATES

A bi-monthly newsletter with updates on data and computing news and events for UW-Madison researchers.

In the August 7, 2019 update:

  • 2019 Biohealth Summit
  • Upcoming Campus Events
  • Upcoming Training and Workshops
  • Campus Opportunities and Groups
  • External Opportunities

Are you…

  • 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 (facilitator@datascience.wisc.edu) 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.


2019 Biohealth Summit

Join 500+ biohealth professionals at BioForward’s annual Biohealth Summit, featuring keynotes and professional development opportunities designed for students and young professionals, including Ryan Jenkins international-recognized generational and future of work keynote speaker. Dr. Elizabeth Burnside and Ms. Karely Yoder will provide the morning keynote and compare the use of imaging and artificial intelligence within their fields. There will be chances to meet and network with industry peers, executives, investors, and researchers from organizations such as GE Healthcare, FUJIFILM, UW-Madison, Illumina, Versiti, Covance, Medical College of Wisconsin, Promega, Advocate Aurora Health, Exact Sciences, UW Health and more! UWHealth is sponsoring free registration for up to 50 students interested in attending. Use code: UWHEALTH19 and select the student ticket type. Free tickets are first come first serve.


Upcoming Campus Events (Calendar View)

Systems, Information, Learning, and Optimization (SILO) Seminar, 4:00pm-5:00pm, Orchard View Room, Discovery Building
Aug 8, Species Tree Reconstruction from Locus-Based Data Under Gene Duplication and Loss, Brandon Legried


Upcoming Training and Workshops

Intro to R and RStudio for Genomics (Day 3 of Genomics Data Carpentry)
This hands-on workshop (August 12, 8:30am – 4:30pm) teaches basic concepts, skills and tools for working more effectively with genomics data using R and RStudio. The workshop is for any researcher who has data they want to analyze, and no prior computational experience is required. There is still some space in this extra carpentry session. Interested participants can register for the third day only at this link. Event hosted by the Data Science Hub.

Software Training for StudentsRoom B1144A, DeLuca Biochemistry Building, 420 Henry Mall (Registration required).
     Excel 1, August 8, 5:00-7:00
     Premiere Pro, August 9, 5:00-7:00

Data Carpentry for Ecology, 8:30am – 12:00pm, 9/4, 9/11, 9/18, 9/25, and 10/2
This hands-on workshop teaches basic concepts, skills and tools for working more effectively with data acquired in Ecology research. The workshop is for any researcher who has data they want to analyze, and no prior computational experience is required. Event hosted by the Data Science Hub. Registration opens at 5:00 pm on August 14, 2019.

Data Wrangling Sessions in Python
“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. Data wrangling is a critical skill for research. This course teaches wrangling skills using mostly the data wrangling tools of the Pandas package. Pandas is a collection of functions/methods for working with data similar to R’s tidyverse. The course dates are 8/19, 8/20, 8/21, 8/22, and 8/23 (9:00 – 1:00). 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.

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. Data wrangling is a critical skill for research. This course teaches wrangling skills using the tools of the tidyverse. The tidyverse is a collection of R packages that are designed to make it easier to work with data. The ggplot2 package is just one example of the highly regarded tools in the tidyverse. The course dates are 8/26, 8/27, 8/28, 8/29, and 8/30 (9:00 – 1:00). 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 8/26 from 10:30-12:30 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. Data wrangling is a critical skill for research. In this class you’ll learn how to wrangle data using Stata. We’ll cover some of the key concepts and workflows of data science as well as the structure and logic of Stata. We’ll emphasize real-world issues like handling missing data and checking for errors, as well as best practices for research computing and reproducibility. Our goal is to give you a strong foundation you can build on to become an expert data wrangler. The course dates are 8/27, 8/28, 8/29,  and 8/30 (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.


Campus Opportunities and Groups

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 8/16 from 3:00-4:30 at the Memorial Union Terrace. This is one in a series of semi-monthly meetings.

DevOps System Admin in SMPH Radiology IT
The Radiology IT department of the School of Medicine and Public Health is looking for a well-qualified DevOps candidate to collaborate on the web development and informatics teams. This is a position for someone who is passionate about developer tools, container technology, automating workflows and helping to create software that ultimately improves patient care. Applications close August 25, 2019.

Research Data Lifecycle Manager
DoIT has an opening for a Research Data Lifecycle Manager in the Research Cyberinfrastructure group. The person in this role will collaborate with other research-serving groups on campus to provide services and practices to help researchers manage their data across the various phases of the data lifecycle. Applications close August 19, 2019.

Help Desk Coordinator with the Libraries
The Library Technology Group, part of the UW-Madison General Library System, is seeking a motivated, service-focused individual to join our operations team and provide responsive and courteous customer service, technical support, and student supervision for the Help Desk. This position will play a key role in the day-to-day operations and services of the help desk, which is the main point of contact for library staff, faculty, researchers, and students. Applications close August 19, 2019.

Machine Learning for Medical Imaging (ML4MI) Bootcamp
We are pleased to announce that we will be hosting a Machine Learning for Medical Imaging (ML4MI) bootcamp, as part of the broader ML4MI initiative. This is a repeat of the bootcamp held last summer and has the goal of giving participants a rapid, hands-on introduction into the principles and application of machine learning for medical imaging. This bootcamp is supported by the Grainger Institute of Engineering and the Departments of Radiology and Medical Physics. The bootcamp will be held August 22-23, 9am-1pm in WIMR 1022. Registration is required. Please feel free to contact the organizers (Kevin JohnsonAlan McMillan, and Tyler Bradshaw) with questions.

BME Design Projects Wanted
UW-Madison Biomedical Engineering (BME) student teams are available to work on solving medical problems by creating prototypes to meet your personal, medical practice, or research needs through the unique BME Design curriculum. Interested? Submit applications by August 14.

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.


External Opportunities

Postdoctoral Researchers in Computational and Statistical Genetics
Applications are invited for Postdoctoral Researchers to join Matthew Stephens’s research group within the departments of Human Genetics and Statistics at the University of Chicago. Research in the Stephens lab focuses on the development and application of statistical tools for the analysis of genetics and genomics data. Ongoing research topics include genetic association studies and analysis of data from single cell transcriptomes. Applicants should send a CV, Research Statement, and names of 3 referees to mstephens@uchicago.edu. Review of applications will begin immediately, and continue until positions are filled.

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.

Microsoft Investigator Fellowship
This year Microsoft is expanding its funding support for academic research by creating the new Microsoft Investigator Fellowship. Submissions are now being accepted, and full-time faculty members must submit their proposals by August 16, 2019. The new Microsoft Investigator Fellowship is a two-year fellowship for full-time faculty at degree-granting colleges in the United States who are currently conducting research, advising graduate students, teaching in a classroom, and use or plan to use Microsoft Azure in research and/or teaching. The award is a $100,000 annual stipend awarded annually for two years starting in Fall of 2019. For questions, please contact Microsoft Investigator Fellowship Program InvestigatorFellow@microsoft.com.

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.


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 newsletter@datascience.wisc.edu.