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Fully-funded Masters+PhD (1+4) Scholarship
Full tuition fees + Annual stipend (£19,237 p/a).
UK-domiciled (Home fee status) applicants only.
Deadline: 15 March 2025
Master / PhD Students / PostDoc: Work with me
I often get requests from students who wish to do their Master (MS/MSc) or PhD thesis with me. This page aims to answer the most common questions, which tend to be about two main categories: topic and funding.
If you contact me via email, please be aware that I receive an absurd amount of email per day. If I do not reply in one week, I may have overlooked your email or it may have been deleted by a SPAM filter. Please resend it again, perhaps from a different email address and/or without attachments (PDF attachments are better than DOC or DOCX or ZIP).
Supervised PhD students
- Seyed Mahdi Shavarani, Quantitative Models of Realistic Human Decision-Makers for Data Analytics and Optimisation, Lecturer at Kent Business School, University of Kent, UK
- Andreea Avramescu, Data-driven Optimization for Personalized Medicine Development and Delivery, Director of Technology and Learning Experience at IN4 Group
- Mudita Sharma, Learning to Control Differential Evolution Operators, AI Data Scientist at Fisher Jones Greenwood LLP
- Lucia Rivadeneira, Decision Modelling Driven by Twitter Data: A Case Study of the 2017 Presidential Election in Ecuador, Information and Statistics Coordinator of GADM Portoviejo, Ecuador.
- Leonardo CT Bezerra, A Component-wise Approach to Multi-objective Evolutionary Algorithms, Lecturer at University of Stirling, UK; previously, Professor at Universidade Federal do Rio Grande do Norte, Brasil (Publications)
- Leslie Pérez Cáceres, Automatic Algorithm Configuration, Associate Professor, Escuela de Ingeniería Informática, Pontificia Universidad Católica, Chile (Publications)
- Jérémie Dubois-Lacoste, Anytime Local Search for Multi-Objective Combinatorial Optimization: Design, Analysis and Automatic Configuration, CEO and Co-Founder of Cryptosphere Systems (Publications)
Master Thesis
Research topics
For a Master thesis, I'm happy to supervise a wider range of topics, as long as they are related to my research interests. An excellent Master thesis should aim at producing a scientific contribution worth publishing on a peer-reviewed conference or journal, but publication is never a requirement. Some general ideas would be:
- Applications of optimization methods to real-world problems are always welcome, including surveys, modelling, implementations of existing or new methods, the creation of benchmarks, comparisons between methods, etc.
- If you have some basic programming experience, given an existing optimization method, apply it to a problem to which it has never been applied.
- Proving or modelling aspects of the behaviour of optimization algorithms, if you have a mathematics background.
- If you have strong qualitative background and you are willing to learn the basics of quantitative methods, then analysing a real-world scenario and its opportunities for optimisation would be interesting.
- If you are not sure about the topics above, but you have a good level in programming in C, C++, R or Python, you are competent in using GNU/Linux, you are interested in optimization problems and/or machine learning and not afraid of challenges, please contact me. I have many other ideas and projects in mind that may interest you.
You can find in my CV the titles of the theses I have already supervised. However, don't hesitate to propose ideas different from the above.
Funding
- Every year, I supervise a number of MSc theses for the MSc Business Analytics: Operational Research and Risk Analysis and MSc Data Science, for which there are some scholarships available.
- International students can apply for various funding schemes
- International students with their own funding are welcome to contact me.
PhD Thesis
Research topics
- Mathematical optimisation applied to real-world problems in logistics, manufacturing, planning, routing, timetabling, finance, business, management, etc.
- Automatic algorithm configuration and design. See [LopDubPerStuBir2016irace], [BezLopStu2015tec], [LopStu2012tec].
- Multi-objective local search. See [DubLopStu2015ejor], [DubLopStu2011amai].
- Machine Decision Makers.
- Algorithmic components and design choices in meta-heuristics. See [LopStu2012swarm], [MarMasLop2013hm]. Read the following paper carefully: http://dx.doi.org/10.1016/j.ejor.2013.09.045. If you understand what is done and why it is important, and you think you could do similar work in your thesis, please talk to me.
- Visualisations of the Empirical Attainment Function
- Operational optimisation of Water Distribution Networks
- Statistical formal analysis of stochastic algorithms and parameter tuning, hence, applications of design of experiments, sequential testing, statistical models, multi-variate statistics, surrogate-models, etc.
- If you are not sure about the topics above, but you have a good level in programming in C, C++, R or Python, you are competent in using GNU/Linux, you are interested in optimization problems and/or machine learning and not afraid of challenges, please contact me. I have many other ideas and projects in mind that may interest you.
Funding
- Alliance Manchester Business School offers a number of fully-funded PhD studentships. Make sure you meet the entry requirements; propose a challenging topic and select the funding source that is best aligned with your proposed topic. When applying, please choose PhD Business and Management. This is an organizational topic, and it doesn't affect the topic of your thesis. Note that the deadlines shown in the webpage may be outdated; better ask the Doctoral Programmes Office.
- The School of Computing also offers fully-funded PhD studentships. Topics in optimization and machine learning are welcome. In this case, you will have to identify an additional supervisor from the School of Computing willing to co-supervise you together with me.
- The University of Manchester has a number of funding sources.
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