Data Science Education Intern | R for Epidemiology

 Stage · Stage autre  · 4 mois (renouvelable)    Bac+3 / Licence   The GRAPH Network, Geneva, Switzerland · Geneva (Suisse)  Compensation will be discussed during the interview process.

 Date de prise de poste : 1 octobre 2023


R Data Science Education


The rapid collection, analysis, and communication of data is a cornerstone of public health.
However, a variety of bottlenecks obstruct the traditional pipelines that should produce
adequately trained health data analysts in many countries.

The GRAPH Network has received a grant to build and deliver online courses that will
empower public health professionals with expertise in modern programmatic tools for
working with health data. Courses currently developed and the learning platform can be
reviewed at this URL:

Tasks and Responsibilities:
Responsibilities will include some or all of the activities below.
● Assist in building engaging course materials that teach R skills for epidemiology
(including text tutorials, video demos, practice quizzes, and summative
● Facilitate clear and accurate translations of learning materials into French.
● Engaging with potential and actual users to understand needs and address feedback.
● Assist in the design and customization of the online learning management system
which hosts the training material.
● Mentoring other interns or external contributors.

Position Assignment: Set between 50% (half-time) and 100% (full-time) capacity based on
the share of tasks that candidates are qualified to perform.

Qualifications, Skills, and Experience
● At least one year of experience using R, Rmarkdown, and the Tidyverse
(“Experience” can include time spent learning these tools.)
● Background in Epidemiology, Health Sciences, or a similar field
● French fluency (Native or C1/C2 proficiency)
● English fluency ( B2, C1, or C2 proficiency)
● Teaching experience (i.e., tutoring)
Perks of the Role
● Flexible hours
● In-office or Remote work option (to be negotiated on a case-by-case basis)
● Collaborative learning environment with transdisciplinary Global Health team.
● Opportunity to grow together with passionate individuals who aim to transform
public health data science education.


Procédure : Application Process: Interested applicants should email the following materials to 1. A CV or resume 2. Evidence of R expertise. This could be a project whose development you led, a StackOverflow profile, a GitHub account, or a published or in-progress first or second-author paper.

Date limite : 30 septembre 2023

Offre publiée le 29 août 2023, affichage jusqu'au 30 septembre 2023