A 3-year PhD studentship in deep-learning assisted design of active hyperuniform materials
Supervisors: Dr Giorgio Volpe (UCL), Dr Yuan Cheng (IHPC, A*STAR, Singapore), and Dr Ran Ni (NTU, Singapore)
Application deadline: 20 July 2020
Start Date: 28 September 2020
Location: London (1.5 years), Singapore (2 years)
Topics: deep learning, soft matter, active matter, photonics, self-assembly, computational sciences
The Studentship
This position is fully funded by the UCL-A*STAR Collaborative Programme
via the Centre for Doctoral Training in Molecular Modelling and
Materials Science (M3S CDT) at UCL. The student will be registered for
a PhD at UCL where he/she will spend year 1 and the first six months of
year 4. The second and third years of the PhD will be spent at the
A*STAR Institute of High Performance Computing in Singapore. The
Studentship will cover tuition fees at UK/EU rate plus a maintenance
stipend about £17000 (tax free) pro rata in years 1 and 4. During years
2 and 3, the student will receive a full stipend directly from A*STAR.
In addition, A*STAR will provide the student with one-off relocation
allowance. Please note that, due to funding restrictions, only UK/EU citizens are eligible for this studentship.
The Project
Hyperuniform materials are a novel class of disordered materials with
properties of both liquids and solids. Because of this dual nature,
such materials are increasingly interesting for photonics as they can
influence the path of light with the efficiency of a crystal while
retaining the flexibility of a liquid. The aim of this collaborative
project is to develop an efficient computational framework to design
optimal hyperuniform materials whose structure can be rearranged
dynamically into different configurations capable of unique interaction
with light. In particular, this project will develop a new efficient
numerical scheme based on the power of deep-learning approaches with
neural networks to realize efficient modeling and design of active
hyperuniform materials. If properly designed, this level of tunability
is promising to realize novel robust functional materials for photonics
and beyond.
The Candidate
The successful applicant should have or expect to achieve at least a
2.1 honours or equivalent for undergraduate degree in Chemistry,
Physics, Materials Science, Engineering or a related discipline. The
successful applicant will demonstrate strong interest and
self-motivation in the subject, excellent programming skills (in C++,
Matlab, Python or equivalent) and the ability to think analytically and
creatively. Good computer skills, plus good presentation and writing
skills in English, are required. Previous research experience in
contributing to a collaborative interdisciplinary research environment
is highly desirable but not necessary as training will be provided.
Please contact Dr Giorgio Volpe (g.volpe@ucl.ac.uk) or Dr Yuan Cheng
(chengy@ihpc.a-star.edu.sg) or Dr Ran Ni (r.ni@ntu.edu.sg) for
further details or to express an interest.
Applications will be accepted until 20 July 2020 but the position will be filled as soon as an appropriate candidate is found.