Sunday, May 31, 2015

[DMANET] PhD Studentship in game theory and machine learning

PhD Studentship in game theory and machine learning
£14,057 Stipend pa

School of Electrical Engineering, Electronics and Computer Science

Closing date for receipt of applications: Wed, 17 Jun 2015 17:00:00 BST

Fully funded Phd position in Game Theory and Machine Learning

This position is defined in the context of the recently started Ariadna
study at the computer science department of the university of Liverpool, in
collaboration with the Advanced Concepts Team (ACT) of the European Space
Agency (ESA): 'Game Theoretic Analysis of the Space debris Removal
Dilemma' This study aims to analyse space debris removal activities from a
strategic, game-theoretical perspective. Space debris is defined as
non-manoeuvrable, human-made objects orbiting Earth. In some orbits, space
debris poses a significant collision risk for an operational spacecraft,
especially in low-Earth orbit (LEO). Currently, there are more than 23,000
objects larger than 5-10cm in Earth orbit.

Within the Clean Space initiative ESA is investigating active debris
removal in addition to mitigation measures to keep the growth of space
debris limited. In cooperation with the national space agencies and
industry partners, ESA is developing mission concepts to clean up and
deorbit space debris. This study contributes to this initiative.
Specifically, the objective is three-fold, one, to model debris
accumulation and active removal efforts as a dynamic game, two, to
determine the optimal time-dependent policies or behaviour assuming both
cooperative and self-interested players, and three, to propose a mechanism
to steer the dynamics of the game to a desirable outcome. It is expected
that such a study will provide a deeper understanding of the space debris
problem and its potential (economic) ramifications, and will provide an
outlook on potential game-theoretic solution strategies.

The investigation will involve mostly (evolutionary) game theory, machine
learning, mechanism design and some experimental simulation work.

The candidate must have a passionate interest in game theory and/or machine
learning, and an interest in space applications.

Prospective candidates must have at least a 2.1 or above Bachelor degree in
a relevant subject (Computer science, Physics, Economics) and should enjoy
mathematical work. Good programming skills are required.

The funding covers EU/UK fees and stipend of approximately £14,057pa for a
total of 3 years. For informal enquiries please contact prof. dr. K. Tuyls
( or dr. R. Savani (
Students can Apply online via our website please state
research council funding & quote 'CS/KTRS'

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