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PhD Student fellow

Infectious Diseases Institute

Research, Teaching & Training

NGO, NPO & Charity UGX Confidential
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1 week ago

Job Summary

he She Data Science (SHEDS) project is pleased to invite suitable applications from females for two fully funded PhD fellowships for the year 2024. SHEDS is a collaborative initiative between the African center of Excellence in Bioinformatics and Data Intensive Sciences(ACE), Infectious Diseases Institute (IDI), Makerere University, Kampala, Uganda and the Institute of Global Health Sciences (IGHS) at the University of California San Francisco (¬¬¬¬UCSF), USA.

  • Minimum Qualification: Masters

Job Description/Requirements

General Summary
Call for applications: Fully Funded PhD Fellowship Opportunities for Females at Makerere University
Empowering Uganda’s Women in Health Data Science: Identifying Barriers, Bridging Knowledge and Innovation for Tangible Impact: She Data Science (SHEDS)

Call open: May 13th, 2024
Call closes: June 20th, 2024
Proposed start: September 2nd, 2024

The She Data Science (SHEDS) project is pleased to invite suitable applications from females for two fully funded PhD fellowships for the year 2024. SHEDS is a collaborative initiative between the African center of Excellence in Bioinformatics and Data Intensive Sciences(ACE), Infectious Diseases Institute (IDI), Makerere University, Kampala, Uganda and the Institute of Global Health Sciences (IGHS) at the University of California San Francisco (¬¬¬¬UCSF), USA.

About the SHEDS program
The increasing adoption of technologies like mobile phones, high throughput genomic sequencing, IoT and electronic health records is accelerating the buildup of an avalanche of data: clinical, genomic, epidemiological, climate-related and social/behavioral data. These growing volumes and complexity of data, render the rapidly expanding field of “Big Data” analysis and interpretation essential to improving health and economic outcomes.

Data Science (DS¬¬¬), which encapsulates Machine Learning and Artificial Intelligence (AI) provides a pathway to the leveraging and enhancement of these data into meaningful and actionable information. However, the highly technical nature of DS as well its powerful potential, simultaneously pause the risk of ‘leaving behind’ sections of the population that have already been disadvantaged. In Uganda in particular, the high gender disparity within STEM fields means that women are more likely to be left behind, resulting in the unintended consequence of DS further widening the gender gap in STEM.

This program is thus going to target the training and advancement of Ugandan women in data science and (or) bioinformatics. It achieves this goal through three critical areas: 1) Skilling women in data science / bioinformatics methods and techniques, 2) identify barriers to women in STEM, Data Science and bioinformatics 3) Providing a bridge to help trainees translate their data science skills into biomedical and public health practice.

Benefits of the program
• There are two fully funded PhD fellowships that will provide tuition and a stipend for a duration of upto 3 years.
• Spend upto 3 months at UCSF, USA in a data science related research lab with a paid economy class return ticket, accommodation and stipend for stay at UCSF.
• Institutional IRB fees for PhD project.
• UNCST fees for PhD project.
• Open Access Publication fees for up to 2 publications.
• World class health data science mentorship from some of the best mentors in the field.

Research concept
The research concept should be one that employs data science, mathematical and (or) bioinformatics to any of the following areas: a) Antimicrobial resistance (AMR) including the design of antimicrobial drug combination therapies, identifying One Health AMR transmission pathways, and utilizing data science methodologies to guide antimicrobial stewardship initiatives; b) Human Genomics including the role of repeats in the human genome; c) cancer including cancer genomics and genomics data science; and d) Natural Language Processing (NLP) and (or) generative AI solutions for health problems.

Submission
Submit the following documents as a single pdf file
1. Certified copies of relevant academic documents.
2. Two reference letters from academic referees.
3. Statement of motivation (max 1500 words).
4. Your idea for the research project (single page).
5. An updated CV (max 4 pages).

Application deadline: June 20th 2024
NB:
• This is a full-time PhD fellowship. It is expected that the intending applicant is not involved in any other form of study or employment.
• Only successful candidates will be notified.

Key Responsibilities

• Fully develop a research concept that employs data science, mathematical and (or) bioinformatics to any of the following areas: a) Antimicrobial resistance (AMR) including the design of antimicrobial drug combination therapies, identifying One Health AMR transmission pathways, and utilizing data science methodologies to guide antimicrobial stewardship initiatives; b) Human Genomics including the role of repeats in the human genome; c) cancer including cancer genomics and genomics data science; and d) Natural Language Processing (NLP) and (or) generative AI solutions for health problems.
• Successfully defend your research proposal
• Successfully obtain ethics approval from Institutional Review Board (IRB) and National approval from Uganda National Council for Science & Technology (UNCST)
• Succesfully complete placement at a research lab at UCSF
• Present your work at scientific workshops, conferences and research forum
• Succesfully defend your PhD thesis
• Write at least 2 peer reviewed scientific publications in high impact journals by the end of the PhD
• Participate in ACE research groups relevant to your area of study.

Person Specification
Eligibility
• Female.

• Minimum qualifications: Applicants should have a bachelor’s degree in a quantitative or health related field with at least an upper second class AND have completed a master’s degree in a quantitative field such as bioinformatics, data science, computer science, mathematics or a related field from a recognized university.
• Be enrolled in a PhD in bioinformatics, data science, computer science, mathematics or a related field at Makerere University and having completed the first year of coursework evidenced by an admission letter and testimonial for first year grades.
• Demonstrated interest in health data science, mathematical modelling and (or) bioinformatics.
• A viable and innovative research concept in any of the above-mentioned areas.
• Ready to commit as a full time PhD student

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