Justice Trésor N. Ngom
3 months ago
Postdoctoral Fellowship in Data Science, Machine Learning, and Health Data Analysis at Stellenbosch University Stellenbosch University in South Africa
Degree Level
Postdoc
Field of study
Computer Science
Funding
The fellowship is funded, with up to two postdoctoral fellowships available. Specific details about stipend amount, duration, or tuition coverage are not provided in the announcement.
Deadline
Expired
Country
South Africa
University
Stellenbosch University

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About this position
Stellenbosch University, a leading institution in South Africa, is offering a Higher Health Postdoctoral Fellowship through its School for Data Science and Computational Thinking. This opportunity is designed for ambitious postdoctoral scientists interested in applying data science and machine learning to improve the health and well-being of tertiary education students and staff. The fellowship focuses on establishing and analyzing data pipelines for Higher Health, with the goal of identifying actionable interventions to enhance health outcomes across the South African higher education sector.
Key research areas include data science, machine learning, predictive modeling, and health data analysis. Successful candidates will lead the design and implementation of data pipelines, integrate data from various sources, and develop predictive models using Higher Health datasets. Responsibilities also include conducting research on student and staff health, publishing high-quality research, and contributing to teaching and school activities.
Applicants should have a PhD in a relevant field such as data science, computer science, statistics, or machine learning, with demonstrated expertise in integrative data analyses and a strong publication record. The fellowship is funded, though specific financial details are not provided. Up to two fellowships will be awarded. For more information and application instructions, candidates are encouraged to consult the official call and visit the provided links.
Funding details
The fellowship is funded, with up to two postdoctoral fellowships available. Specific details about stipend amount, duration, or tuition coverage are not provided in the announcement.
What's required
Applicants must hold a doctoral degree (PhD) in a relevant field such as data science, computer science, statistics, machine learning, or a related discipline. Candidates should demonstrate expertise in integrative data analyses, experience in designing and implementing data pipelines, and the ability to conduct research on health-related topics. Strong publication record and ability to contribute to teaching and activities at the School are preferred. No specific GPA or language test requirements are mentioned.
How to apply
Review the detailed call for applications in the attached PDF. Prepare your application materials as specified by the School for Data Science and Computational Thinking. Visit the provided links for more information. Submit your application as instructed in the official call.
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