Funded Scholarships: Research Degrees

If you are interested in any of the below scholarships, please apply via our normal Programme links (Full time or Part Time) but ensure that you very clearly indicate on your cover letter or personal statement that you would like to be considered for a particular scholarship.

 


PhD Studentship in Logic and Verification at UCL

A PhD studentship in the area of logic and verification is available at UCL's PPLV group. The studentship is aligned with the IRIS project (https://uclirisproject.wordpress.com) and will be supervised by Professor David Pym (http://www.cs.ucl.ac.uk/staff/D.Pym/)and Dr. James Brotherston (http://www0.cs.ucl.ac.uk/staff/J.Brotherston/).

The area of the studentship is in logic and its application to program and systems verification, with a particular interest in the development and application of logical tools based on bunched logic, separation logic, and concurrent separation logic (and related ideas) and their use to reason about the correctness of interfaces between programs, systems, and organizations. The project may range from theoretical work in logic (semantics and proof theory) through the theory of system modelling tools to the design and implementation of modelling and verification tools. 

The PPLV group conducts world-leading research in logical and algebraic methods and their applications to program and systems modelling and verification. The Interface Reasoning for Interacting Systems (IRIS) project, led by Prof. David Pym, uses logical and algebraic methods to understand the compositional structure of systems and their communications, seeking to develop analyses at all scales, from code through distributed systems to organizational structure, generically and uniformly. 

The IRIS project, funded as a UK EPSRC Programme Grant, is a collaboration involving James Brotherston, Byron Cook, George Danezis, Peter O’Hearn, and David Pym at UCL, Alastair Donaldson at Imperial College, Will Venters at LSE, and Edmund Robinson at QMUL. Industry partners include Amazon AWS, BT, Facebook, HP Labs, GridPP, and Methods Group. 

Candidates should normally have or be about to complete a Master's level qualification in mathematics or computer science, with a strong component in logic or theoretical computer science. 
The studentship is available from September/October 2018. Candidates should be UK or EU nationals. 
Interested candidates may contact David Pym (d.pym@ucl.ac.uk) or James Brotherston (j.brotherston@ucl.ac.uk) for more information. 

To apply, please follow the instructions at http://www.cs.ucl.ac.uk/prospective_students/phd_programme/applying/

Deadline for Applications: 27th May 2018


PhD Studentships in Human-Computer Interaction at the UCL Interaction Centre

Applications are invited for a PhD studentship in the UCL Interaction Centre (UCLIC, https://uclic.ucl.ac.uk/), funded by a Horizon 2020 project grant focussed on crowd navigation of robots. The PhD studentship is to support the design of a crowd-aware smart, with a focus on human-robot interaction. The scholarship is for up to 3 years from June 2018, and covers tuition fees at the UK/EU level, and a stipend at the standard EPSRC rate. 

Eligibility

Please be aware this funding is only available to UK/EU candidates who have (a) settled status in the UK, with no restrictions on how long they can stay and (b) been 'ordinarily resident' in the UK for 3 years prior to the start of the studentship (for education purposes is fine). For more information: http://www.epsrc.ac.uk/skills/studentships/help/eligibility/

Person Specification

The successful applicant will possess a strong bachelor’s degree (1st or 2:1) or Master's degree in Human-Computer Interaction or a related discipline. Candidates will ideally have some relevant previous research experience, including working and designing with disabled people, and should have excellent communication and presentation skills.

Project Details

CROWDBOT (aka “Safe Robot Navigation in Dense Crowds”) is a EUR 4M Horizon 2020 consortium of 5 universities and 2 industrial partners: INRIA, France (co-ordinator); EPFL, Switzerland;

ETHZ, Switzerland; RWTH, Germany; UCL, UK; SBR Europe, France; and LOC GmbH, Germany.

CROWDBOT brings together world-leading robotics experts to develop the next-generation of robots capable of navigating crowded environments. UCL will lead a core workpackage on the co-design and evaluation of the CROWDBOT system, as well as developing one of the demonstrators: a crowd-aware smart wheelchair. This project complements several of our ongoing projects and initiatives by adding new capabilities to overcome some of the barriers to translation of smart wheelchairs beyond the lab/clinic: the ISI4NAVE Inria associated team, which investigates innovative sensors and interfaces; the INTERREG VA ADAPT project, which is creating a smart powered wheelchair platform and training simulator; the GDI Hub, which aims to improve the lives of disabled people worldwide; Aspire Create, a partnership between UCL Faculty of Medical Science, UCL Faculty of Engineering, the Royal National Orthopaedic Hospital and the Aspire Charity, which aims to develop technology to improve quality of life for people living with spinal cord injury; UCLIC, which is a world leading Centre of Excellence in Human-Computer Interaction; and Queen Elizabeth Olympic Park, which is fast becoming a world leading test bed in the invention and trialling of new approaches to meeting the global city-based challenges of our time of which establishing clean, efficient and accessible ways to move people and goods around our city is one.

PhD Details

Interactions with semi-autonomous wheelchairs

The PhD studentship is co-supervised by Dr Cathy Holloway by Dr Tom Carlson. The principle aim of the PhD project is to develop the state of the art of human-robot interactions (HRI) whilst developing a semi-autonomous wheelchair that will adapt its trajectory to unexpected movements of people in its vicinity. It is expected that the PhD project will advance any of the following aspects of HRI:

1) The development of novel interactions for the wheelchair user which result in a better driving experience and greater independence

2) The development of semi-autonomous wheelchair that can move in crowded environments

3) Exploration of the differences in perception of the public to robots which are clearly driven by someone and one which is autonomous

4) The role of emotion in HRI 

Start Date: October 2018

Application Procedure

Applications should submit their applications through the online UCL Select system 

1. A personal statement and research proposal describing the preferred research question, a summary of some relevant literature, and an outline of the type of research to be conducted (including ideas about which methods would be appropriate).

2. Examples of academic writing and outputs from past work (e.g. a dissertation or assignment)

3. Academic transcripts

4. A CV

Questions about the studentship can be made to the individual academics listed with each project. Queries about the application process can be made to Sarah Turnbull: s.turnbull@ucl.ac.uk 

Application Deadline: 7th June 2018


PhD scholarship: Analytics-driven Software Engineering and Search-based Software Engineering

A fully-funded PhD scholarship is available under the supervision of Dr. Federica Sarro (http://www0.cs.ucl.ac.uk/staff/F.Sarro/) at the Computer Science Department of University College London (UCL), UK.

The successful applicant is expected to research novel methods equipping software engineers with search-based and analytics techniques and tools to better drive their day-to-day decisions and to switch from a “gut feel” to an “evidence-based” approach in crucial Software Engineering activities including, but not limited to, project management, requirements elicitation, and software testing.

This PhD scholarship represents an exciting opportunity to delve into an important and timely research area on a border of software engineering, optimisation and data science, and are well-suited to students with a strong interest and aptitude in the application of artificial intelligence, predictive analytics, machine learning and optimisation techniques to software engineering problem. A PhD within this area will prepare the candidate to undertake academic research career and industrial research and development IT career in Software Engineering.

Skills and Prerequisites

We look for a highly motivated candidate with a bachelor’s degree with first or upper second-class Honours, and/or a distinction at master’s level in Computer Science, Software Engineering, Machine Learning or a closely related subject, and preferably with a strong interest and background in software engineering, data analytics or optimisation, and solid programming skills. Applicants with other qualifications and sufficient relevant experience and background knowledge may be considered. All the applicants should meet the admissions criteria for the UCL Department of Computer Science (CS) PhD programme: http://www.cs.ucl.ac.uk/prospective_students/phd_programme/entry_requirements/.

What We Offer

The successful PhD candidate will receive a strong career development support, will have access to a robust doctoral research training programme, dedicated research resources, training in transferable skills, visiting speaker seminar programme, conference allowance, and will be associated with well-renowned research centres and groups at UCL (CREST,SSE,UCLAppA). In addition, PhD students will be encouraged to undertake training and development in teaching and deliver teaching/research assistantship duties on a paid basis to further enhance their experience in preparation for their future career.

The student will also enjoy a very welcoming and multicultural community: UCL is proud of its longstanding commitment to equality and to providing a learning, working and social environment in which the rights and dignity of its diverse members are respected. For more information about UCL and its CS Department, you can watch short videos about the life as a student at UCL and our research vision, and have a look at the CS web site.

How to Apply

Applications should be made formally by following the standard UCL admission process: http://www.cs.ucl.ac.uk/prospective_students/phd_programme/applying.

Please apply here and indicate clearly on your cover letter or personal statement that you are applying for this studentship specifically and name Dr. Federica Sarro as the potential supervisor.

Applicants are strongly encouraged to include in their personal statement a description of the research they aim to carry out in any of the following areas: Predictive Models and Data Analytics for Software Engineering, App Store Mining and Analysis, Search Based Software Engineering.

Informal enquiries and expression of interest can be made by e-mail to Dr. Sarro (f.sarro@ucl.ac.uk).

The next deadline for applications is April 27th, 2018 (for a September 2018 start).


PhD Studentship: Automated black-box verification of networking systems

Our society is increasingly reliant on complex networking systems, consisting of several components that operate in a distributed/concurrent fashion, exchange data that may be highly sensitive, and are implemented with a mix of open and closed-source code. Examples are Software Defined Networks, cloud computing systems, Internet of Things and others. 

As the complexity of these systems increases, there is a pressing need of methods and tools to automatically verify security and privacy properties. High quality models – able to express all the behaviours of interest – are of paramount importance to this aim. However, it is often the case that the task of building a model is performed by humans and in a short span of time – if it is performed at all – and as such can be error-prone and inaccurate. 

The goal of the proposed PhD project is to develop techniques and tools to automate the modelling and verification of networking software systems. The novel idea is to rely on the model learning paradigm, originally proposed in artificial intelligence, to automatically build an automaton model of a running system in a black-box fashion -- purely via interactions with the running system.  

The PhD project is funded by the UK Research Institute in Verified Trustworthy Software Systems (VeTSS), and will be supervised by Prof. Alexandra Silva and Dr. Matteo Sammartino. The start date can be negotiated and should be September 2018 at the latest.

Potential applications are encouraged to contact Prof. Silva (alexandra.silva@ucl.ac.uk) or Dr. Sammartino (m.sammartino@ucl.ac.uk) for expressions of interest or further information.

 


PhD Studentship: EPSRC project - Automated Software Specialisation Using Genetic Improvement

A fully-funded PhD studentship is available under the supervision of Dr. Justyna Petke (http://www0.cs.ucl.ac.uk/staff/J.Petke/). The student will be required to undertake research in software engineering that is relevant to Dr. Petke's fellowship on automated software specialisation.

The project will utilise and develop novel methods in the field of software engineering, called genetic improvement. GI is a novel field of research that only arose as a standalone area in the last few years. Several factors contributed to the development and success of this field, one of which is the sheer amount of code available online and focus on automated improvement of non-functional properties of software, such as energy or memory consumption. Work on automated software transplantation using GI had already gathered multiple academic awards and media attention with coverage in BBC Click and the Wired magazine, among others.

The goal of the project is to transfer the challenging and time-consuming task of software specialisation from human to machine. It will develop novel approaches for specialising and improving efficiency of generalist software for particular application domains in an automated way. More details are available at the following website: gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/P023991/1.

Informal enquiries can be made by email to Dr. Petke (j.petke@ucl.ac.uk).

Prospective PhD students must apply through the standard UCL admission process (http://www.cs.ucl.ac.uk/prospective_students/phd_programme/applying).

The next deadline for applications is April 27th.

 


PhD Studentship: Networking and Systems

A PhD studentship is available under the primary supervision of Dr. Stefano Vissicchio. The position is fully funded for 3.5 years.

Following a tradition of the group, the studentship will be co-supervised by Mark Handley or Brad Karp.

The position is not bound to any specific grant or project.

We therefore invite applications from talented, highly motivated students eager to work on any topic of interest for the group, including modern network architectures and paradigms like SDN and NFV; distributed, centralised and partially centralised network management systems; inter- and intra-domain routing; network monitoring, testing and security; Internet measurements.

Prospective PhD students must apply through the standard UCL admission process, in which a committee of academics drawn from the breadth of the department evaluates the entire pool of applicants.

For a September 2018 start, the next and last deadline for applications is April 27th.

More information about the application process are reported at http://www.cs.ucl.ac.uk/prospective_students/phd_programme/applying/

Interested candidates are also welcome to contact Dr. Stefano Vissicchio at s.vissicchio@ucl.ac.uk for further information, and to discuss about more concrete project proposals.

Please apply here indicate clearly on your personal statement or research proposal that you are applying for this studentship specifically.

 


PhD Studentship:Understanding, Measuring and Improving the Security of Collaboration Tools

Whenever you communicate with someone electronically there are intermediaries that process and carry your communication, helping it reliably get to the intended destination, or storing it until the recipient goes online to collect it. We hope that these intermediaries behave properly, but sometimes they get hacked, or the people running them act maliciously, and your communications can then be tampered with and eavesdropped, with potentially severe consequences. End-to-end encryption is designed to protect against such threats and has been available for decades, but it’s still rarely used because it interferes with modern ways of working. For example, if the company that provides your email service can’t read it, you can’t search it without downloading it all; with collaboration applications, like Google Docs or chat applications, current end-to-end encryption approaches won't even work. Even if data is encrypted end-to-end, analysis of the meta-data can still violate privacy, for example disclosing who is working with whom. Anonymous communication systems like Tor can help protect meta-data but the delay that the most secure systems (e.g. Loopix) introduce would prevent standard collaboration technologies from working properly. This project will develop techniques to build collaboration applications that are end-to-end secure, and protect privacy. We will quantify how secure and effective they are, working with investigative journalists who need high levels of security in their collaboration applications.

 

 

Funding is available for a 4-year PhD studentship working on this project, providing a standard stipend and fees (at UK/EU rate). The project will be supervised by Dr Steven Murdoch and will start in October 2018 (unless agreed otherwise).

 

To apply click here and indicate your interest on your cover letter. To be considered for this scholarships, please submit your application no later than the 27th April 2018.

 


PhD Studentship: Categorical Semantics of Probabilistic Graphical Models

Project description

Scientists in diverse areas of computer science (and beyond) use graphical formalisms in order to specify and study systems based on interacting components. Graphics outperforms textual information in highlighting connectivity and resource-exchange between parts of a system. This makes diagrammatic languages particularly effective in the analysis of subtle interactions as those found in cyber-physical, concurrent and quantum systems. 

In recent years a uniform mathematical approach to these formalisms emerged, based on the language of monoidal category theory and informed by the compositional methods of programming language semantics. Whereas this perspective have been fruitfully applied to systems appearing in various contexts (especially quantum and control theory), it is at a preliminary stage when it comes to the analysis of probabilistic graphical models, such as Bayesian networks. 

The surge of interest in machine learning and probabilistic programming makes these models particularly relevant to current research. This project will develop a compositional semantics for probabilistic graphical models based on symmetric monoidal categories. Algorithms and methodologies for tasks such as Bayesian learning and inference will be analysed within this new framework, which hopefully will provide a more transparent mathematical foundation and formal proof methods.

The project’s trajectory is not set in stone. Categorical approaches to network diagrams constitute an exciting and vital research areas, with possibility of connecting to diverse research fields. For instance, the formal methodologies developed in the initial stage of the project could rather inspire developments in the formal semantics of cyber-physical systems and digital circuits. This will depend by how the student’s research interest develops.

Skills and Prerequisites

This is a project in theoretical computer science. It requires an interest in using the mindset of category theory to explore (Bayesian) probability theory. If the candidate is not already familiar with category theory, at least some background in basic logic (syntax and semantics) is required. Other useful background knowledge is denotational semantics of programming languages, formal language theory (regular languages, automata) and universal algebra. 

Formalities

University College London (UCL) offers a fully funded scholarship to undertake this project in the Programming Principles, Logic and Verification Group, for a full three years, extensible to a fourth year if necessary. The scholarship will be awarded to the student who meets the UCL admissions criteria for the UCL Department of Computer Science PhD programme and who best suits the project. 

The main supervisor will be Dr. Fabio Zanasi. Applicants are encouraged to visit Zanasi’s webpage (http://www0.cs.ucl.ac.uk/staff/F.Zanasi/) for getting an idea of his research activities, and to contact him by email for any enquiry/expression of interest. The starting date can be negotiated but should be between February 2018 and September 2018.

During the PhD, the student will be encouraged to visit the supervisor's collaborators (located in UK, Italy and the Netherlands) both for training and research purposes.

 

To apply click here and indicate your interest on your cover letter

 


PhD Studentship (x3): European research Council EPIC (Evolving Program Improvement Collaborators) project

The UCL CREST centre (http://crest.cs.ucl.ac.uk/about/) is offering up to three fully funded PhD studentships in the general area of Search Based Software Engineering (SBSE (https://en.wikipedia.org/wiki/Search-based_software_engineering)) to start September 2018.

The studentships will be on the European Research Council (ERC) Advanced fellowship grant EPIC (Evolving Program Improvement Collaborators) project, held by Mark Harman.

The key idea is that evolutionary computation can evolve software  improvement collaborators; automated tools that offer specifically-evolved, explained and experimentally-justified  advice on software improvements that optimise operational performance, while maintaining and/or extending functionality.

This "Epi-Collaborator" will make suggestions, including transplantation of code from a donor system to a host, grafting of entirely new features grown (evolved) by the Epi-Collaborator, and identification and optimisation of tuneable deep parameters. A key feature (and an important scientific and technical challenge for the project) is that these suggestions need to be backed by automatically-constructed quantitative evidence that justifies, explains and documents improvements.

EPIC thereby aims to introduce a new way of developing software, as a collaboration between human and machine, integrated into typically continuous integration code review repo frameworks. Rather than seeking to replace human intelligence with artificial intelligence, EPIC thus seeks to understand and exploit the complementary strengths of each: humans' domain and contextual insights and machines' ability to intelligently search large search spaces.

The EPIC project and these studentships are funded by the award of an ERC Advanced Grant to Mark Harman, who will supervise the students, together with a supervisory team, including Dr. Federica Sarro (http://www0.cs.ucl.ac.uk/staff/F.Sarro/) and Dr. Earl Barr (http://earlbarr.com), both also eminent software engineering researchers at UCL.

Prof Harman is a professor of Software Engineering at UCL but also an engineering manager at Facebook London (https://research.fb.com/people/harman-mark/), where he manages the team working on the application of SBSE to automated software test design. Prof. Harman’s joint appointments foster the collaboration between academic research and industry application, where students may see the impact of their research at Facebook scale.

The closing date for applications is 27th April 2018.

Any enquiries to Professor Harman (Mark.Harman@ucl.ac.uk).

To apply click here and indicate your interest on your cover letter.