Data+ is a 10-week summer research experience that welcomes Duke undergraduates interested in exploring new data-driven approaches to interdisciplinary challenges. Students join small project teams, collaborating with other teams in a communal environment. They learn how to marshal, analyze, and visualize data, while gaining broad exposure to the modern world of data science.

ASA DataFest^TM is a data analysis competition where teams of up to five students attack a large, complex, and surprise dataset over a weekend. Your job is to represent your school by finding and communicating insights into these data. The teams that impress the judges will win prizes as well as glory for their school. Everyone will have a great experience, lots of food, and fun!

This mini-class will introduce the student to machine learning methods that have become increasingly useful in practice, specifically deep learning and neural networks. Application areas include image and text analysis. This will not be a traditional class with a priori and regular scheduled class times. Rather, over the course of the semester, students participating in this class will be required to attend at least 5 two-hour in-person learning experiences (IPLEs) provided by the Duke +DS program.

Using computers to generate art promotes deeper understanding of the ways that artificial intelligence (AI) is changing the visual and media-based world around us, and provokes inquiry into the endeavor and humanity behind creativity. In this spirit, +DS is excited to announce the second annual Duke AI for Art Competition.

New Spring 2020 Class Offering Training in AI to All Duke Students: This class will introduce the student to machine learning (ML) and artificial intelligence (AI) methods that have become increasingly useful in practice, specifically deep learning and neural networks. Application areas include image analysis, text analysis, and optimal decision making. This class is directed to any Duke student, independent of major, who is interested in learning the basics of ML and AI.

+DS program team members Matthew Kenney, Ricardo Henao, and Shelley Rusincovitch are project sponsors for the summer 2020 Story+ project "Critical Decisions: Perceptions of AI in Healthcare Management."

Story+ is a 6-week paid summer research experience for Duke students—undergraduates and graduates—interested in exploring humanities research approaches (archival research, oral histories, narrative analysis, visual analysis, and more).

CS+ is a ten week summer program for Duke undergrads to get involved in computer science research projects with faculty in a fast-paced but supportive community environment. Students participate in teams of 3-4 and are jointly mentored by a faculty project lead and a graduate student mentor.

ASA DataFest^TM is a data analysis competition where teams of up to five students attack a large, complex, and surprise dataset over a weekend. Your job is to represent your school by finding and communicating insights into these data. The teams that impress the judges will win prizes as well as glory for their school. Everyone will have a great experience, lots of food, and fun!

ASA DataFest 2020 will take place at Duke over the April 3 - 5 weekend. Sign up by March 19, 2020 at 11:59p!

The Margolis Scholars program is a prestigious program for Duke University students that demonstrate strong interest in and commitment to a career in health policy and management, as well as leadership potential to improve health policy. Named in honor of Robert Margolis, M.D., the founder of Duke-Margolis and a pioneer of innovative integrated care delivery models, the Margolis Scholars program provides promising students with the necessary knowledge, skills, and abilities to be the next generation of health care leaders.

The Duke University Department of Statistical Science and the Duke AI Health Institute are co-sponsoring the ASA Datafest: COVID-19 Virtual Data Challenge. For this contest, student will work in teams to seek out publicly available data sources that enable them to explore the societal impacts of the COVID-19 pandemic other than those directly related to health outcomes. Contest submissions will be due on April 22, 2020.

Muser provides Duke students with regularly-scheduled, clearly articulated, and equitable access to research opportunities across all fields. Muser Round for Summer 2020 projects is now underway. For students, Friday, April 24 at 8:00am is the first day to apply for projects, and Friday, May 1 at 11:59pm is the last day to apply for projects.

The +DS Fall 2020 Virtual Research Program is designed to allow students who have previously completed the +DS curriculum to continue their engagement with substantive applied projects. The +DS Advanced Projects in Health Data Science offer Duke students, both undergraduate and graduate, the opportunity to be a part of research teams applying advanced machine learning (deep learning) to important areas of medicine. The students will work in teams, mentored by leading Duke faculty involved in data science research, with guidance by practicing clinicians.

The Durham Department of Veterans Affairs (VA) is now accepting applications for its Big Data Training Enhancement Program (BD-STEP), a 1-2 year postdoctoral training opportunity offered through the National Cancer Institute (NCI) and the Veterans Health Administration (VHA) to enhance experience while addressing oncology-related research questions relevant to Veterans using the U.S. VA’s extensive real-world clinical oncology data. 

Overview
Data+ is a ten-week summer research experience that welcomes Duke under- graduates interested in exploring new data-driven approaches to interdisciplinary challenges.

In research and clinical applications such as transcranial magnetic stimulation, brain machine interface, and closed-loop neural stimulation there is increasing need to record brain signals (electroencephalography, local field potentials, single neuron spiking) immediately after electric or magnetic stimulation of the brain. However, the electromagnetic artifact corrupts the neural recording after the stimulus pulses.

Transcranial magnetic stimulation (TMS) is a noninvasive method for modulating brain function. It is used widely in brain research and is FDA cleared for the treatment of several psychiatric and neurological disorders. Unlike drugs, TMS can be targeted to specific regions of the patients’ brain. Doing this accurately, however, requires expensive and uncomfortable systems for navigation of the TMS coil (“neuronavigation”).

Currently, naturalistic or drug-induced behaviors in mice have to be coded by hand.  The goal of this project is to use SLEAP (https://sleap.ai/) and to score certain behaviors in mice, for which we already have live video recordings.  If successful, we may move to a 3-dimensional AI program.  The project will be overseen by two faculty, one experienced with rodent behavior and the other with writing/using AI programs.  The project can be accomplished virtually.  This can be an individual project.

The program is designed to allow students who have previously completed the +DS curriculum to continue their engagement with substantive applied projects. The +DS Advanced Projects in Health Data Science offer Duke students, both undergraduate and graduate, the opportunity to be a part of research teams applying advanced machine learning (deep learning) to important areas of medicine. The students will work in teams, mentored by leading Duke faculty involved in data science research, with guidance by practicing clinicians.

Duke-Margolis addresses critical health policy challenges with innovative, evidence-based solutions to improve health and the value of health care. Our interdisciplinary approach brings students and faculty from Duke’s schools of medicine, nursing, law, public policy, business, and engineering together with policy experts, researchers, and health care professionals across the country to work together on focused projects that make a difference.

The Duke Summer Computing Institute is a 6-week virtual learning experience open to any undergraduate studying engineering or science.

You're invited! No affiliation with Duke or previous programming experience is required.

Learning with Duke's expert faculty, build skills in programming, data science and machine learning through an immersive online experience

Duke Undergraduate Machine Learning is happy to announce that we will be hosting a Virtual Machine Learning Day on Saturday, March 27th from 10-4pm EDT. This year’s speakers include Jeff Jonas (founder and CEO of Senzing), Dr. Kyle Bradbury (Managing Director of Duke’s Energy Data Analytics Lab), and more. We will also be hosting a 90 minute virtual poster session in which Duke students conducting machine learning research will present their work and conduct brief Q&A sessions with the audience.

Project Data Sphere® (PDS) is currently seeking summer interns (Masters or PhD student) with a specific interest in AI development using DICOM images. DS is developing regulatory-grade AI algorithms to automate detection and annotations of tumor lesions and to calculate total tumor burden. PDS will be collaborating with academia, pharma, and FDA – it’s a great opportunity which intersects radiology/oncology/computer science/statistics fields. 
 
To learn more about this opportunity, contact AT Tasneem, PhD, Director, Images and Algorithms Program Project Data Sphere® asba.tasneem@projectdatasphere.org

The +DS fall semester research program is designed to allow students who have previous experience in data science to continue their engagement with substantive applied projects. The +DS Advanced Machine Learning Projects in Health Data Science offer Duke students, both undergraduate and graduate, the opportunity to be a part of research teams applying advanced machine learning (deep learning) to important areas of medicine. Participating students will be mentored by leading Duke faculty involved in data science research, often with guidance by practicing clinicians.