This PhD scholarship offers three years’ funding, including tuition fees and a stipend of approximately £15,000 per year for candidates wishing to commence their studies in September 2019. The successful candidate will also receive a generous research support and conference allowance. You will also have access to a robust doctoral research training programme, dedicated research resources, training in transferable skills, visiting speaker seminar programme, and associate with existing research centres and groups.
Students will benefit from state-of-the art facilities at the newly refurbished Business School including a new Learning Resources Centre, Data Analytics Visualisation Lab and a Behavioural Economics and Strategic Management Laboratory. All students are encouraged to undertake training and development in teaching and deliver teaching and/or research assistantship duties on a paid basis to further enhance their experience in preparation for their future careers.
The aim of this PhD project is to develop flexible data-driven/surrogate-assisted/Bayesian optimization methods that, based on data from a time-consuming process simulator, discover robust and cost-efficient manufacturing processes and supply chains in personalized healthcare. In addition to time-consuming evaluations, the optimizer needs to account for other problem features, such as mixed-type decision variables, multiple objective functions and constraints, and noise. Furthermore, user preferences may need to be accounted for during the optimization procedure.
This is a collaborative and interdisciplinary project providing the student with academic and industrial guidance in terms of resource-constrained optimization, drug manufacturing, supply chain management, and multi-criteria decision making. The student will have the opportunity to validate the methods developed in a real world environment.
The potential impact and benefit of this project goes beyond simply academic achievements and commercialization. The innovation resulting from this project has the potential to move the reality of targeted healthcare forward and contribute to a step change for many patients in terms of widened access to new treatments.
The candidate will be supervised from the Decision and Cognitive Sciences Research Centre, and link with the School of Computer Science (University of Manchester) and notable groups in the UK and Europe.
Applications for this project are sought from exceptional UK, EU and international students with an outstanding academic background in a quantitative subject such as Computer Science, Mathematics and Operations Research. The successful candidate must have a strong programming background (Python/C/C++/Java/R) and good analytical and communication skills. An understanding of expensive (surrogate-assisted/Bayesian) optimization and/or multi-criteria optimization/decision-making is highly desirable.
Applicants must have a First or Upper Second Class Honours degree (or equivalent) and hold or expect to obtain a Masters level qualification with Distinction. English Language requirements (where required) are IELTS 7.0, TOEFL 623 (100 ibt), PTE 66.
How to apply
Candidates should submit a PhD application for the PhD Business & Management and indicate that they wish to be considered for this project.
Your application must contain a 3000-word research proposal related to the topic.
Candidates are strongly advised to submit their application as early as possible. Candidates who do not submit the required supporting documents by the specific deadlines will not be considered.
Application deadline: 29th March 2019
For further details about the project, please contact Dr. Richard Allmendinger at email@example.com.
For questions related to making your application, please contact Lynne Barlow-Cheetham in the Doctoral Programmes Office: firstname.lastname@example.org