Wednesday, February 1, 2023

Applications Now Open for Big Data Summer Institute 2023!


Through its Big Data Summer Institute program, the University of Michigan is committed to helping to build the next generation of leaders who will explore the intersection of Big Data with biology, medicine and public health. Please share information about this program with undergraduate students (spring 2024 or later expected graduation date) who are passionate about biostatistics, statistics, mathematics, electrical engineering, computer science, biomedicine, public health or any related field. Thank you!

PDF Flyer for 2023 Big Data Summer Institute

Transforming Analytical Learning in the Era of Big Data

An Undergraduate Summer Institute in Biostatistics (SIBS) at the University of Michigan

JUNE 20 - JULY 28, 2023

Application Now Open! Deadline to apply is March 15, 2023

This full-time, in-person six-week summer institute will introduce undergraduate students to emerging challenges at the intersection of Big DataStatistics, and Human Health.

Lectures will be led by a diverse group of stellar biostatisticsstatistics, electrical engineering, and computer science faculty at the University of Michigan. Faculty from biomedicine and public health will present their perspective of big data.

Working in teams, students will participate in mentored big data research projects.


We think the Big Data Summer Institute is an exceptional experience. But don't just take our word for it. Here's what past participants have to say about their experience.



NHLBI Summer Institute in Biostatistics Program - Grant R25HL147207

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Monday, January 30, 2023

Institute for Statistical and Data Science: Panel Data Methods and Causal Inference - 4 livestreaming seminars


Institute for Statistical and Data Science


Instats is dedicated to helping researchers tackle their data-analytic challenges by providing hands-on training and expert consulting

Featured Structured Course
Instats is pleased to announce a series of 2-day seminars on panel data modeling and causal inference with difference-in-differences (DiD) methods. These are being offered in collaboration with professors Jeffrey Wooldridge and Malvina Marchese in their four-part course Panel Data Modeling: From Static Models to DiD Estimation and Causal Inference using Stata.

The first two seminars cover basic and advanced panel data methods by professor Marchese: Panel Data Models and Methods in Stata (Feb 16 - 17) and Advanced Panel Data Modeling with Stata (Mar 2 - 3),  including the nonlinear case. Malvina is a great communicator and educator in this area, so don't miss out on this opportunity to learn about the most modern methods for analyzing panel data!

The next seminars by professor Wooldridge introduce methods for causal inference, and then synthesize this with panel data models by covering DiD methods: Causal Inference with Cross-Sectional Data (Mar 22 - 23) and Difference-in-Differences (DiD) Methods with Panel Data (April 5 - 6), including recent cutting-edge applications. As many of you may know, Jeff is one of the best known and most cited econometricians, so it is a real treat to be able to host his seminars — and he’s agreed to stay on the Zoom sessions at the end of each day to continue chatting if you’d like!

By registering for this four-part course, you will gain a comprehensive understanding of panel data modeling, alongside methods for causal inference with cross-sectional and panel data. Registering for all 4 seminars also provides a 10% discount, which is in addition to the very affordable pricing that Instats already offers — especially for PhD students.

Please get in touch with any questions including group discounts with 5 or more, and please tell your colleagues, students, and friends about this once in a lifetime opportunity to learn directly from these experts!
Malvina Marchese Senior Lecturer and Visiting Professor Bayes (formerly Cass) Business School, City University of London & NTNU University, Norway
Malvina Marchese Senior Lecturer and Visiting Professor Bayes (formerly Cass) Business School, City University of London & NTNU University, Norway
Jeffrey Wooldridge University Distinguished Professor of Economics Department of Economics, Michigan State University
Jeffrey Wooldridge University Distinguished Professor of Economics Department of Economics, Michigan State University
Learn More and Register
Structured courses are sets of seminars that offer comprehensive coverage for a range of analysis methods and software, with a 10% discount applied to each seminar in the series. Seminar's can also be registered for separately.
Check out all of our Structured Courses
 Upcoming Live-Streaming Seminars
Live-streaming seminars are delivered over 2 days and include interactive tutorials, discussion, and activities. To enable asynchronous learning, recordings of all sessions and instructor support are available for 30 days.

February 6, 7 & 8

Instructor: Dr Jonas Lang
Business School, University of Exeter and Journal of Applied Psychology

The hands-on course teaches basic and intermediate multilevel techniques used in the social and organizational sciences in an accessible manner. The course relies on the free software R and the modeling packages lme4 and nlme along with help functions and datasets from the multilevel library (Bliese, 2021). Topics include (1) aggregation models and the use of agreement and reliability statistics like the ICC1, ICC2, and rwg, (2) model specification and interpretation of “standard” multilevel models used in organizational research (data centering, random slopes, interaction effects), (3) graphical methods to examine model assumptions, and (4) useful extensions of the standard model to test phenomena such as cross-classified multilevel models and consensus emergence in groups. When purchasing the seminar you will be freely enrolled in an on-demand seminar on multilevel SEM in Mplus by Professor Zyphur, helping you to extend your multilevel learning and offering a substantial value. An official Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, each seminar offers 2 ECTS Equivalent points.

February 8, 9 & 10

Instructor: Dr Mike Cheung
Department of Psychology, National University of Singapore

This seminar introduces the basic theory of meta-analytic structural equation modeling (MASEM) and illustrates how to conduct the analyses with R. Meta-analytic structural equation modeling (MASEM) is an incredibly powerful tool for hypothesis and theory testing, relying on pooled correlation matrices from primary studies, and this seminar will teach you the basics of MASEM and how to apply it in your own research, using many hands-on examples with Professor Cheung's R package for MASEM. When purchasing the MASEM seminar you will be freely enrolled in two on-demand seminars that introduce the logic of path analysis and CFA/SEM in R by Professor Zyphur, offering a substantial value. An official Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers 2 ECTS Equivalent points.

Instats Statistics Seminars and Courses

Thursday, January 26, 2023

Internship Opportunity: Nevada National Security Site (NNSS) Undergraduate Science Internship (Associate in Science - Levels I - IV)

 Nevada National Security Site (NNSS)

Undergraduate Science Internship (Associate in Science - Levels I - IV)
Undergraduate Science Interns will work under the direct supervision of a manager & mentor and will be provided with hands-on participation in ongoing projects at one of the most unique experimental sites in the United States, or one of our outlying location sites.
Duties and Responsibilities (may include and will vary depending on which department you are assigned to):
  • Build programming code/scripts to computationally process image and/or signal data, e.g. in Python, Matlab, or R. Knowledge of image/signal processing techniques is desired.
  • Create and give presentations on both project and progress to teammates and management.
  • Contribute towards professional reports and papers.
  • Potential for participating in hands-on data acquisition activities depending on project.
  • Participate on small teams of scientists, engineers, and technicians, to devise technical solutions and provide deliverables to customers.
  • Perform hands-on work on optical, mechanical, and/or electrical systems including data acquisition and system and/or subsystem fabrication.

Job Opportunity: Nevada National Security Site (NNSS) - Rotational Data Scientist I / Data Scientist II

 Nevada National Security Site (NNSS)

Rotational Data Scientist I / Data Scientist II
Are you interested in working with some of the brightest talent in the world to strengthen the United States’ security? Come join the Nevada National Security Site (NNSS) where our employees apply their expertise to create solutions for high-hazard and highly complex experiments that help us keep the planet safe.
The NNSS’s Science and Technology (S&T) Directorate is seeking early career scientists to engage with our national security mission in research, development, and experimentation. You will have the opportunity to work on teams that ensure the security of the United States and its allies by: supporting the stewardship of the nation’s nuclear deterrent; contributing to key nonproliferation and arms control initiatives; executing national-level experiments in support of the National Nuclear Security Administration’s National Laboratories; working with national security partners such as the Department of Defense, the Intelligence Community, and other federal agencies on important national security activities; and providing long-term environmental stewardship of the NNSS’s Cold War legacy.
As a member of the S&T Directorate’s Computing & Data Sciences division, you will work collaboratively with a diverse group of colleagues on challenging problems of national significance, with opportunities to work in the experimental field and engage with a broader team of scientists and engineers. Multiple positions are available across a spectrum of experience levels, with benefits and requirements requisite with experience and educational background.
Data Scientist I
  • Have experience with, or interest in learning, at least one of the following areas:
    • Developing and applying state-of-the-art analysis techniques to laboratory and field research. Areas of interest include software engineering, software design, mathematical modeling, statistics, Bayesian analysis, machine learning, applied physics, numerical analysis, uncertainty quantification, experiment design, edge computing, and algorithm development for communications in harsh environments.
    • Learning and running existing analysis codes to plan and analyze experiments and incorporate experimental data analysis techniques.
  • Develop algorithms, field experiments, and deploy analysis techniques to experiment data from complex diagnostic measurement systems.  
  • Actively participate with scientific, engineering, and technical teams supporting experimental platforms, including the Subcritical Experiment Program in the underground U1a Complex.
  • Fulfill project objectives as a in highly multidisciplinary teams exercising sound judgment in collaboration with peers.
  • Promote diversity, equity, and inclusion within the program.
  • Perform other duties assigned by Management.

Summer Institute in Biostatistics and Data Science Information


Summer Institute in Biostatistics and Data Science 

Program Overview 

The Summer Institute in Biostatistics (SIBS) and Data Science is sponsored jointly by the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute of Allergy and Infectious Diseases (NIAID). The comprehensive six to seven week summer training course on biostatistics and principles of data science combines classroom learning with career mentoring and hands-on data analysis using data collected from clinical studies in prevention and treatment of infectious, immune-mediated, and chronic diseases. Designed to address a growing imbalance between the demand and supply for biostatisticians and data scientists, the course targets undergraduates and beginning graduate students who are interested in learning about biostatistics, and encourages them to consider graduate programs related to biostatistics and data science. The typical curricula include an intensive introduction to biostatistical approaches and research by exposing participants to the principles, methodologies, uses, and applications of statistical methods in biomedical and clinical research.

NIH Summer Institute in Biostatistics Flyer

For the upcoming session of 2023, NHLBI and NIAID will collectively support the SIBS programs including:

Boston Universityexternal link link

Columbia Universityexternal link link

Florida Atlantic Universityexternal link link

North Carolina State University-Duke Universityexternal link link

University of California Irvineexternal link link

University of Colorado Denverexternal link link

University of Iowaexternal link link

University of Michiganexternal link
http://bigdatasummerinstitute.comexternal link

University of Southern Californiaexternal link link

University of Texas Medical Branchexternal link link

Program officials:

Sean Coady
Epidemiology Branch
National Heart, Lung, and Blood Institute
National Institutes of Health
6701 Rockledge Drive, MSC 7936
Bethesda, Maryland 20892
Phone: 301-435-1289
Email: coadys@nhlbi.nih.govmailto:

Misrak Gezmu
Biostatistics Research Branch, Division of Clinical Research
National Institute of Allergy and Infectious Diseases
National Institutes of Health
5601 Fishers Ln, MSC 9820
Rockville, MD 20892 
Phone: 240-669-5232

Link to the information above: