Category Archives: Academic

NRSG 736: Quantitative Analysis of Clinical Research Data, Fall Course

Course Description

The course objective is to build and expand upon the statistical theory and methods learned in BIOS 500 and 501 and improve the student’s statistical software experience and programming skills (emphasis on SAS, SPSS or R) to improve their research scholarship and dissemination. All exercises and homeworks provide the analysis codes in SAS, SPSS and R which is a great way for students who know one programming language to easily learn the others at the same time (this is a benefit not a requirement).

The course focuses on practical application of statistics addressing clinical research questions. Analyzing data is the major emphasis of the course including examining if assumptions of the statistical analyses are being met and interpreting the findings.  Course assignments and a final project focus on using statistical software and computing resources to analyze data sets from actual clinical research studies and literature with interpretation and assessment of conclusions.

 

Course Details 

  • Instructor: Melinda Higgins, Ph.D.
  • Meeting Times: Mondays 11:00-11:50am; Wednesdays 1:00-2:50pm 
  • In class/computer lab time: 1 hour lecture; 2 hours computer lab per week 

 


Emory Foundations for Online Teaching Course

Description 

Emory Foundations for Online Teaching (EFOT) is a professional development opportunity for graduate students offered through a joint partnership between the Center for Faculty Development and Excellence and the Emory Center for Digital Scholarship. Emory graduate students from any school are welcome to enroll. EFOT introduces best practices for online teaching and is designed for graduate students who are preparing to TA or teach partially or wholly in an online environment.* All course sessions use Canvas, and the participant learns from the point of view of an online student. Participants must have a computer with Internet and Zoom access. This course and its sessions are taught 100% online.

Successful completion of the program may be helpful to students interested in teaching or serving as a teaching assistant in the Emory College of Arts and Sciences.

Participants will learn about:

  • best practices for and methodology behind online teaching
  • instructional design
  • tools and technologies
  • Emory resources for online education.

Modules focus on:

  • teaching using a learning management system
  • pedagogically sound course design
  • developing learning objectives and assessments for the online environment
  • synchronous and asynchronous communication techniques
  • building an online community.

 

Course Schedule

  • May 24th- July 5th, 2021

 

How to Apply 


Computational and Data Science Fellowships, ACM

***Current first years eligible***

 

Description 

ACM SIGHPC has created the Computational and Data Science Fellowships, a continuation of the program started with Intel to increase the diversity of students pursuing graduate degrees in data science and computational science. Specifically targeted at women or students from racial/ethnic backgrounds that have not traditionally participated in the computing field, the program is open to students pursuing degrees at institutions anywhere in the world.

Each fellowship recipient will receive a stipend prior to the start of their first academic term after August 1. The value of the stipend will be US$15,000 annually, adjusted depending on the country where the degree will be earned (using the most recent national price level ratio published by the World Bank). This stipend is intended to augment, not replace, the support already being provided by the institution. Recipients will receive the stipend annually for up to 2 years, as long as they are deemed to be making appropriate progress in the degree program (progress will be evaluated annually by ACM SIGHPC based on a brief report from each recipient). If additional funding becomes available, fellowship winners may be given the opportunity to receive extended support (through the completion of the degree, but not more than five years total).

  • Nominations for the 2021 class open: March 15, 2021
  • Nominations for the 2021 class close: April 30 , 2021
  • Winners announced: by June 24, 2021 

 

Eligibility 

To qualify for a Computational & Data Science Fellowship, a student must be:

  • Either currently enrolled in a graduate program or accepted to begin in one no later than October 15
  • Pursuing a graduate degree – Master’s, PhD, or equivalent – in computational or data science (although the formal name of the program may be somewhat different)
  • Completed less than half of her/his planned program of study (with preference given to students who are still early in their studies)
  • A woman and/or a member of a racial/ethnic group that is currently underrepresented in the computing field in the country where the student will earn the degree

For the purposes of these fellowships, “computational science” encompasses any program of study where computational modeling and simulation serve as the primary methods for conducting research, typically in a field other than computer science (e.g., computational chemistry, wildfire modeling, computational hydrodynamics). Similarly, “data science” relies on computational analysis of large-scale data as the basis for research (e.g., ecological informatics, financial analytics). Preference will be given to candidates whose background is from disciplines other than computer science and who can bring new perspectives to computational/data science.

 

Application Information 

Applications for the fellowships involve three independent components and must be submitted using SIGHPC’s online nomination system:

  1. Nomination: submitted by the student’s advisor (or soon-to-be advisor), who will explain how the candidate qualifies for a fellowship
  2. CV and candidate statement: submitted by the student, along with contact information for an endorser
  3. Brief endorsement: submitted by a current or former instructor, project supervisor, or employer who has personal knowledge of the student’s past accomplishments and can speak to the candidate’s suitability

All components must be submitted in sequence, and completed no later than April 30. See how to nominate for details. In accordance with ACM policies on conflict-of-interest, the following are ineligible to serve as nominators or endorsers: officers of ACM and members of the Fellowship Selection Committee.

 

How to Apply 

Click here to read more about this fellowship opportunity and apply online! 

 

 


American Public Health Statistics 2021 Student Competition

Opportunity Description 

The APHS Section is accepting abstract submissions for student research poster and oral presentation sessions. Students wishing to be considered for these sessions should submit online an abstract and a 2-page summary of their paper. In order to be eligible for the student competition you must be a student at the conference in October 2020 (those graduating in May/June 2020 are not eligible). When submitting your abstract, please submit it under the session “Student oral presentations” or “Student poster presentations”, even if it may be thematically related to other topics on the topic list.

Click here to learn more about the competition!

 

How to Enter & Additional Information

Students interested in competing in the student oral paper competition should contact Dr. Niloofar Ramezani (nramezan [at] gmu [dot] edu) Your two-page summary of the paper should be e-mailed to Dr. Niloofar Ramezani (nramezan [at] gmu [dot] edu) with a copy to Dr. Haresh Rochani (hrochani [at] georgiasouthern [dot] edu),  with a letter from a faculty member attesting to the author’s student status.

If a student abstract was submitted for oral presentation but is not accepted as an oral presentation, it will automatically be considered as a poster submission. All accepted student abstracts will be considered for the Student Research Competition. An award will be given for the Best Student Oral Presentation.


Adopt-a-Scholar Program Scholarship for First Years

Description

The Adopt-a-Scholar Program provides financial assistance to outstanding RSPH students who demonstrate exemplary leadership, community service involvement, academic success, and commitment to a career in public health. Below are the Adopt-a-Scholar Program Scholarships that are available:

  • Dr. Edgar Simard Scholar ($2500 Award):Preference for this award will be given to an outstanding student in Epidemiology.
  • Hardman Family Scholar ($2500 Award):Preference for this award will be given to an outstanding student passionate about working on environmental issues, with a focus on climate and health.
  • Mitchell Family Scholar ($2500 Award):Preference for this award will be given to an outstanding student who has a special interest in childhood food allergies, nutrition, or food insecurity.

 

Eligibility 

  • Applicants for the Adopt-a-Scholar Program must be current MPH/MSPH students with a 3.5 GPA or higher.
  • Selected students will receive a scholarship to be applied towards their tuition.

 

How to Apply 

Please use this link to complete your scholarship application by our deadline of Friday, March 5, 2021 at 11:59PM EST. 

If you have any questions please do not hesitate to contact:


Biostatistics Online Summer Institute Scholarships, University of Washington

Description 

Scholarship applications are now being accepted for the 2021 Summer Institute in Statistical Genetics (SISG) and the Summer Institute in Statistics and Modeling in Infectious Diseases (SISMID). Like last year, the institutes will be held completely online.

The goal of the Summer Institutes is to strengthen the technical proficiency and career preparation of scholars from all backgrounds, especially those from groups historically underrepresented in STEM such as racial and ethnic minority groups, low income, first generation college students, veterans, and differently abled and 2SLGBTQ groups.

Graduate students attending a U.S. college or university are eligible to apply for SISG modules. All graduate students and postdocs are eligible for SISMID scholarships. 

Contact uwbiost [at] uw [dot] edu if you have questions about any of the summer institutes.

 

Registration & Scholarship Details 

  • General registration will open February 15th for SISG and SISMID.
  • Click here to apply for a scholarship for one of the eligible summer institutes. 
  • The application deadline is March 10th, 2021.

 

 


EH 530: Environmental and Occupational Epidemiology, Spring 2021 Course

Description 

Environmental and Occupational Epidemiology is a course for students in the Environmental Health Department who have successfully completed EPI 530 and BIOS 500. Students will gain experience reading, evaluating, and interpreting epidemiologic studies on the impact of both workplace and environmental exposures, and thinking through practical considerations. The course aims to strengthen each student’s ability to read epidemiological literature critically. This aim will be realized through in-depth exploration of major study designs including cross-sectional studies, cohort studies, and case-control studies, and through the weekly readings and case studies. The focus of the class is on conceptual issues common in environmental and occupational epidemiology research, the application of epidemiological concepts to environmental health topics, and on the interpretation of findings. Successful completion of the course will also contribute to a richer appreciation of how the environment affects public health.

Click here to view the course syllabus! 

 

Course Hours and Location

  • Fridays 3:15 – 5:05 PM
  • Online 

PSYC 770: Multilevel Modeling, Spring 2021 Course

Course Description 

This seminar provides an introduction to multilevel modeling. Multilevel models, also known as mixed, hierarchical, and random-effects models, provide a conceptual framework and an analytic option for working with clustered/nested data (Aarts, Verhage, Veenvliet, Dolan, & van der Sluis, 2014). They allow researchers to study different sources of variation in the outcomes, and the effects of predictors at different and across levels.

This seminar will consider the formulation of statistical models for multilevel modeling applications. The presentations will be conceptual and the instructor will demonstrate analyses using personal computers and provide time for “hands on” practice. We will use the software programs HLM8 (Raudenbush, Bryk, Cheong, Congdon, & Du Toit, 2019), the lmer4 R (Bates, Maechler, B., & Walker, 2015) and the WinBUGS (Lunn, Thomas, Best, & Spiegelhalter, 2000) packages, and SPSS in the seminar. The prerequisite for this seminar is a course on multiple regression.

Click here to read a copy of the course syllabus. 

 

Meeting Information 

  • Class Hours: Tuesdays 9:40 am to 12:35 pm 
  • This class will meet synchronously 

 

How to Enroll 

 


APE Resources

Resource Summary 

As the semester winds down and you all prepare for a different winter break, the Office of Career Development has pulled together some resources for you regarding the applied practice experience (APE).  As you start to plan for this degree requirement, please refer to  the Applied Practice Experience website, which is your primary resource and guide.

The APE Portal is where you will track and receive approvals. To learn more about how to use this platform, view the APE Portal Training.

There are also career development resources and guides posted on the Career Development website as well as Handshake Resources.

Lastly, the Office of Career Development Staff has recorded a few short videos (see  below) to help you with the APE search and process. If you need individual assistance with strategizing, please schedule a one-on-one coaching session or attend a virtual walk-in session, which can be done via Handshake.

 

APE Video Resources


Planetary Health, Spring 2021 Course

Description 

Human beings are profoundly altering the natural systems of the planet, resulting in a variety of unintended population health consequences. This course explores several of the mechanisms by which humans are influencing the physical, chemical, and ecological conditions on the planet, and some of the potential consequences of those ongoing changes in systems for human societies. Although all topics presented in this course are intersectional, the impacts can be broadly grouped into planetary health impacts of ecosystem changes (“biosphere”), and planetary health impacts of geological and atmospheric changes (“geosphere”). Successful completion of this course will refine skills in systems thinking and regard for planetary challenges.

Prerequisites: EH520, EH582 or permission of instructor

 

Course Information

  • Credit Hours: 2
  • Time and Format: Fridays 10:15 – 12:10 PM, Online Course
  • Click here to view the course syllabus!

Upcoming Events

  • EGDRC Seminar: Lynn Aboue-Jaoudé January 14, 2025 at 12:00 pm – 1:00 pm Seminar Series; tinyurl.com… Online Location: https://tinyurl.com/Lynn-Abou-JaoudeEvent Type: Seminar SeriesSeries: Health System Users in Vulnerable Situations: Normative Experiences and “New Ways of Life”Speaker: Lynn Abou-JaoudéContact Name: Wendy GillContact Email: wggill@emory.eduLink: https://tinyurl.com/Lynn-Abou-JaoudeDr. Lynn Abou-Jaoudé studies sociocultural challenges in healthcare experiences, focusing on qualitative research and diabetes prevention at the University of Lille’s LUMEN lab.
  • GCDTR Seminar: Erin Ferranti, PhD, MPH, RN January 21, 2025 at 12:00 pm – 1:00 pm Seminar Series; tinyurl.com… Online Location: https://tinyurl.com/ErinFerrantiEvent Type: Seminar SeriesSeries: Cardiometabolic Risk and Resource Connection in Maternal HealthSpeaker: Erin Ferranti, PhD, MPH, RNContact Name: Wendy GillContact Email: wggill@emory.eduRoom Location: RRR_R809Link: https://tinyurl.com/ErinFerrantiDr. Erin Ferranti, Emory Assistant Professor, researches women’s cardiometabolic disease prevention, health inequities, maternal morbidity, farmworker health, diabetes, and hypertension using biomarkers for early risk identification.

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