Openings

I have currently two open PhD positions, at the Department of Mathematics of King's College London. The starting date for both positions is October 2025. 

1. Supply scenario simulation and optimization in a global complex multi-echelon consumer healthcare supply chain: This project will be focused on the development of novel multi-objective sequential decision-making algorithms on graphs (which are intended to represent the underlying multiechelon supply chain of Haleon with varying granularity levels). The development of the said algorithmic strategies will also rely on the utilization of bespoke simulation software and Haleon's real-world supply chain data to produce realistic, timely, and competitive supply-chain solutions.
   
   The student will be primarily supervised by myself but will also be given access to Haleon's offices and will be expected to interact regularly with Haleon's Data Science team, and externally supervised by Dr. Gueorgui Mihaylov. Note that this position is only open to home students.
   
   Eligibility criteria: This position is open to UK students only. Applicants should have a 2:1 or first-class undergraduate degree, or an MMath, MSci or Master’s degree with Merit and high grades in modules relating to the research area. A solid background in linear algebra, calculus, and probability is expected. A background in optimization, or measure theory would be considered a plus. Additionally, the student is expected to have (or be willing to invest a considerable amount of time to develop) strong programming skills (Python).
   
   For additional information and instructions on how to apply, please visit: https://www.kcl.ac.uk/study-legacy/funding/phd-studentship-supply-scenario-simulation-and-optimisation-in-a-global-complex-multi-echelon-consumer-healthcare-supply-chain
   
   

2. Large-Scale Continuous Nonlinear Optimization: This project will focus on the development and analysis of efficient and robust optimization algorithms for the solution of general or application-directed nonlinear (possibly stochastic, non-smooth, or non-convex) continuous optimization problems of large-scale (i.e., problems with millions to billions to variables). This research will involve deriving novel first- and/or second-order optimization methods, conducting convergence analyses and developing associated efficient implementations.
   
   Eligibility criteria: This position is open to both Home and Overseas students. Applicants should have a 2:1 or first-class undergraduate degree, or an MMath, MSci or Master’s degree with Merit and high grades in modules relating to the research area. A solid background in linear algebra, calculus, and scientific computing/numerical analysis is expected. A background in optimisation, probability or measure theory would be considered a plus. Additionally, the student is expected to have (or be willing to invest a considerable amount of time to develop) strong programming skills, with preferred languages being C++, Julia or Python.
   
   For additional information and instructions on how to apply, please visit: https://www.kcl.ac.uk/study-legacy/funding/phd-studentship-phd-in-large-scale-continuous-nonlinear-optimisation

Further Questions:

Candidates that are interested in working with me, are encouraged to get in touch via email at spyridon.pougkakiotis@kcl.ac.uk by attaching their CV and a short research statement (no longer than 1 to 2 paragraphs).