|Funding for:||UK Students, EU Students|
|Funding amount:||From £17,668 The studentship will cover Home tuition fees plus an annual tax-free stipend, for 3.5 years full-time, or pro rata part time|
|Hours:||Full Time, Part Time|
|Placed On:||2nd December 2022|
|Closes:||28th February 2023|
Data science (DS) and artificial intelligence (AI) have achieved considerable successes in recent years and an ever-growing number of disciplines rely on it. Building effective machine learning (ML) models from data is an integral part of the majority of DS and AI workflows. The complexity of these tasks highly rely on human ML experts thus are often beyond non-ML-experts. The rapid growth of ML applications has created a demand for off-the-shelf ML approaches that can be used easily and without expert knowledge. This is also known as automatic machine learning (AutoML) which automatically obtain a ML pipeline from data and have become an increasingly popular area in the ML community.
In practice, the design of an AutoML system is essentially a multi-objective optimization problem with more than one performance criterion to consider simultaneously. These criteria, such as predictive performance, model size, prediction speed, fairness and interpretability will vary between projects and have inherent trade-offs. ML pipeline is design by human thus should work for human. Unfortunately, only a few efforts have focused on the interaction between human and AutoML. Partially due to this concern, the current AutoML is still another black box for both ML experts and non-ML-experts to use in practice.
In this project, we aim to develop a revolutionary AutoML system that keeps human-in-the-loop. It consists of the following objectives.
Note that the successful PhD student is not expected to carry out all these four objectives in this project but just selected ones pertinent to her/his research interests and experience.
This award provides annual funding to cover Home tuition fees and a tax-free stipend. For students who pay Home tuition fees the award will cover the tuition fees in full, plus at least £17,668 per year tax-free stipend. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee and no stipend.
The studentship will be awarded on the basis of merit for 3.5 years of full-time study to commence on 25th September 2023. The collaboration with the named project partner is subject to contract. Please note full details of the project partner’s contribution and involvement with the project is still to be confirmed and may change during the course of contract negotiations
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