PhD Studentship in Big Data Analytics and Agritech (HARVIST Project)

[Full tuition fee waiver for three years and a stipend each year at £20,780. Applicants who need a student visa must pay for this themselves along with the Immigration Health Surcharge.] 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].