Details
We offer a PhD position working on next-generation computing framework for agroecosystems. Emerging AI paradigms, such as lifelong learning and knowledge-guided machine learning will be explored to support intelligent decision-making, to foster sustainability.
The success of machine learning (ML) in computer vision and language translation where large-scale data is available has led to growing attention in scientific disciplines. However, using purely data-driven ML approaches to modelling physical processes has many limitations such as low interpretability, out-of-sample failure and rich data demand. ML models grounded by explainable theory stand a better chance against learning spurious patterns from data that lead to non-generalizable performance. Moreover, the conventional ML paradigm solves problems in isolation, and it requires building new models from scratch when adapting to multiple heterogeneous landscapes, which is resource-wasteful and time-costly. This problem becomes even worse when there is insufficient data in new landscapes. This project aims to develop a novel ML paradigm that (1) explores the continuum between knowledge-based and ML models, where both scientific knowledge and data are integrated synergistically, (2) empowers ML model with lifelong learning capacity that continually acquires and refines knowledge over a lifetime of experience across diverse landscapes, thereby easily adapting to multiple heterogeneous landscapes when there is insufficient or even no data. The developed AI techniques will be applied in the modelling and prediction of agroecosystem, such as carbon cycle quantification, GHG emissions prediction, and climate forecasting. Finally, these models will be optimised and controlled to derive decisions for fertiliser management, hence ensuring co-sustainability of food production and environmental protection.
Supervisor Bio - https://www.sheffield.ac.uk/dcs/people/academic/tong-liu
Enquiries regarding the project should be sent to Dr Tong Liu. Please add quote [PHD-LifelongAI] in the email subject line.
About the Department & Research Group
The successful candidate will join the Pervasive Computing Research Group at the Department of Computer Science, University of Sheffield. 99 percent of our research is rated in the highest two categories in the REF 2021, meaning it is classed as world-leading or internationally excellent. We are rated as 8th nationally for the quality of our research environment, showing that the Department of Computer Science is a vibrant and progressive place to undertake research.
The Pervasive Computing Research Group focuses on the design, development, deployment and evaluation of pervasive computing methodologies, models, algorithms, tools, and their applications and ethical implications. More details can be found: https://www.sheffield.ac.uk/dcs/research/groups/pervasive-computing
Candidate Requirements
- Minimum 2.1 undergraduate honours degree or Master’s degree with Merit in a relevant discipline (such as Computer Science, Mathematics or others related to the PhD topic), or international equivalent.
- If English is not your first language, you must have an IELTS score of 6.5 overall, with no less than 6.0 in each component.
- Being self-motivated and enthusiastic about doing research in AI and data science.
- Have a good first degree in computer science, mathematics, control/systems engineering, or any-related field.
- Practical experience in a broad range of techniques including data analytics, machine learning, process modelling, optimisation.
- Strong programming skills such as Python, MATLAB.
- Excellent oral and written communication skills.
- Experiences of presenting or preparing scientific manuscripts in journals or conferences is preferred.
How to Apply
To apply for a PhD studentship, applications must be made directly to the University of Sheffield using the Postgraduate Online Application Form. Make sure you name Dr Tong Liu as your proposed supervisor.
Information on what documents are required and a link to the application form can be found here – https://www.sheffield.ac.uk/postgraduate/phd/apply/applying
The form has comprehensive instructions for you to follow, and pop-up help is available.
Funding Notes
This PhD studentship will cover standard UK home tuition fees and provide a tax-free stipend at the standard UK Research Council rate (currently £18,622 for 2023/24) for 3.5 years. If you are an overseas student, you are eligible to apply but you must have the means to pay the difference between the UK and overseas tuition fees by securing additional funding or self-funding. Further information on International fees can be found here - https://www.sheffield.ac.uk/new-students/tuition-fees/fees-lookup