Hafiz Alaka
3 weeks ago
PhD Studentship in Big Data Analytics and Agritech (HARVIST Project) University of Hertfordshire in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Expired
Country
United Kingdom
University
University of Hertfordshire

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Where to contact
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About this position
The University of Hertfordshire is offering a three-year PhD studentship within the Big Data and Innovation Lab, focusing on the HARVIST (Hub for Agricultural Resilience through Value-chain, Irrigation, Storage, and Technology) project. This initiative aims to pilot digitally enabled agricultural ecosystems in Nigeria, integrating solar-powered irrigation, cold storage, traceable logistics, predictive maintenance, and a blockchain-based marketplace. The project is designed to be scalable and franchise-ready, providing a unique opportunity to contribute to agricultural resilience and technological innovation in Africa.
The studentship includes a full tuition fee waiver for three years and an annual stipend of £20,780. Applicants requiring a student visa must cover visa and Immigration Health Surcharge costs themselves. The position is open to UK, EU, and international candidates, reflecting the global relevance of the research.
Successful candidates will engage in developing machine learning models, front end development, and sustainability analysis, working closely with colleagues familiar with the project. The research will involve big data analytics, software development, and data visualization, with a strong emphasis on agritech solutions tailored to African contexts.
Supervision will be provided by Professor Hafiz Alaka and Professor Amin Hosseinian Far, both experts in the field. The project offers interdisciplinary exposure, combining computer science, agriculture, environmental science, business, information technology, and management.
Applicants must hold a Bachelors and Masters in a computing-related discipline, demonstrate knowledge and experience in big data analytics and machine learning (including supervised and unsupervised learning, deep neural networks, support vector machine, BART machine, and generative algorithms), and have practical experience in software development and data visualization. Additional requirements include some knowledge of sustainability, interest in management, and familiarity with agritech solutions in Africa. English language competence (minimum IELTS 6.5 or equivalent) is required for non-native speakers.
To apply, candidates should download the application form from the university website, prepare a research proposal (maximum 2000 words), obtain two academic references, and submit degree certificates, transcripts, CV, personal statement, and a copy of their passport photo page. Completed applications must be emailed to the Doctoral College Admissions team at [email protected] by 24th February 2026 at 9pm. Interviews will be held in the week commencing 5 March 2026, and the studentship will start as soon as possible.
This opportunity is ideal for candidates passionate about leveraging big data and machine learning to drive sustainable agricultural innovation, particularly in African contexts. For further information, visit the Doctoral College website or contact Professor Hafiz Alaka at [email protected].
Funding details
Available
What's required
Applicants must have a Bachelors and Masters in a computing-related course, knowledge and experience of Big Data Analytics, practical experience with machine learning methods (including supervised and unsupervised learning, deep neural networks, support vector machine, BART machine, and generative algorithms), experience in plug-in and software development, knowledge or experience in data visualization, some knowledge of sustainability, interest in management, and interest, knowledge, or experience in Agritech solutions in Africa. Open to UK, EU, and international applicants. English language competence (minimum IELTS 6.5 or equivalent) is required for candidates whose first language is not English. Applicants must submit a completed application form, a research proposal (max 2000 words), two academic references, degree certificates and transcripts, CV, personal statement, and a copy of passport photo page.
How to apply
Download and complete the application form from the university website. Prepare a research proposal (max 2000 words), two academic references, degree certificates and transcripts, CV, personal statement, and a copy of passport photo page. Email your completed application and supporting documents to [email protected] by 24th February 2026 at 9pm. Interviews will take place in the week commencing 5 March 2026.
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