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Applications are closed for September 2020 entry. There are several admissions deadlines in several rounds, until the Centre places have all been filled. Application deadlines for each round are indicated under our Application Timeline. Committed to providing an inclusive environment in which diverse students can thrive, the Centre particularly encourages applications from women, disabled and Black, Asian and Minority Ethnic (BAME) candidates, who are currently under-represented in the sector.

Entry requirements
Applicants will normally be expected to have a distinction at MSc level (or equivalent) in computer science or related discipline. However, in exceptional cases we may consider other qualifications (including at undergraduate level) and all applications will be considered on their merit as appropriate to the individual case. Applications from individuals with non-standard backgrounds (e.g. those from industry or returning from a career break) are encouraged, as are applications from women, disabled and Black, Asian and Minority Ethnic (BAME) candidates, who are currently under-represented in the sector. All applicants will need to demonstrate enthusiasm and aptitude for the programme. 

It is not necessary that an applicant has completed their current course of study before applying. If an applicant has not completed their current course of study, any offer may be conditional on the eventual degree classification.  

Applicants must have a good command of English and be able to apply it in an academic environment. Therefore, those who have not been educated in English will usually be required to provide certificated proof of competence in English language before starting their studies. Applicants should have an IELTS Score of 6.5 overall with a minimum of 6.0 in each skill, or a TOEFL iBT score of 92 overall with a minimum of 23 in writing and 20 in each of the other skills. Equivalent language qualifications may also be considered, see Band D of the King’s College London English Language Requirements, and Accepted English Qualifications in the Imperial College London English Language Requirements.

Fees and funding

The Centre will fund up to 15 studentships each year, depending on the support available. Each studentship will be funded for 4 years. This includes tuition fees, stipend and a Research Training Support Grant (RTSG). 

    • Stipend: Students will receive a tax-free stipend of ca £17,000 per year. 
    • RTSG: A generous allowance will be provided for research consumables and additional training, and for attending UK and international conferences.  
Home & EU students

EU students are eligible to apply for a fees-only award and, dependent on residency in the UK, may be eligible for a full UKRI award inclusive of stipend if they have lived, worked or studied within the UK for 3 years prior to the funding commencing. For 2020/21 entry, UKRI will guarantee such students funding for the duration of their course, even when/if the United Kingdom leaves the EU during this time.

It is expected that there will also be some full studentships (with stipend) available for EU applicants without the residency requirement, and we encourage strong EU candidates to apply.

International students

International students are not normally eligible for these studentships. However, the Centre may occasionally fund outstanding international candidates and we encourage strong international candidates to apply. 

Part-time students

It is possible to apply to the Centre to study on a part-time basis and we welcome applications from people who are unable to study full-time due to managing, for example, caring responsibilities, a disability or chronic illness. Because of the nature of the Centre and its training programme, the demands on part-time students are somewhat different to those made of part-time students on a standard PhD programme. All part-time students enrolled in the Centre are required to: 

  • Be physically present in the department during normal working hours for at least two days a week.
  • Attend all compulsory elements of the Centre, including all training activities and all cohort building activities. This may sometimes necessitate full-time attendance over a period (for example, full-time attendance at the Centre Summer School will be expected over a 3 – 4 day period), and such activities may fall outside a student’s typical part-time hours. (Note that the Centre has a Carers’ Fund, which students may apply to in order to cover caring costs incurred by attendance of Centre activities that fall outside of normal hours.)

Part-time students will be supported by a pro-rata studentship in line with their mode of registration (assuming eligibility for a studentship as per UKRI Terms and Conditions). 

If you are interested in the possibility of part-time study within the Centre please send an email to stai-cdt@kcl.ac.uk in advance of the application deadline in order to discuss this. The Centre is unable to consider part-time applications from applicants who do not do this.  

Students in full-time employment

Applicants should note that it would be exceptional for the Centre to enrol a student who is in full-time employment. It is extremely challenging to manage a standard part-time PhD alongside full-time work responsibilities; Centre students will additionally need to commit to the substantial part-time student requirements outlined above. In order to consider an application from a part-time student in full-time employment (not self-employed), the Centre will require the applicant’s employer to provide a signed letter confirming that they understand and accept the commitments associated with the Centre and are supportive of their employee’s application. 

Students in full-time employment are not eligible to receive a tax-free stipend. They may be eligible to receive a fees-only award, dependent on residency.  

If you are in full-time employment and are interested in the possibility of part-time study within the Centre please send an email to stai-cdt@kcl.ac.uk in advance of the application deadline in order to discuss this.  The Centre is unable to consider part-time applications from applicants who do not do this. 

Self-funded students

We also welcome applications from students (Home/EU/International) who have secured their own funding or are in receipt of alternative scholarships.  

If you are a self-funded student and wish to study within the Centre please send an email to stai-cdt@kcl.ac.uk in advance of the application deadline in order to discuss this. 

How to apply

Identify your three preferred projects from the  available projects for September 2020 entry. It is also possible for applicants to propose their own project, relevant to the area of model-based safe and trusted artificial intelligence as described on these pages. Note that applicants who select at least one project from each institution (King’s College London and Imperial College London) may increase their chance of success by submitting an application to each institution.

You should make an application to King’s College London and/or Imperial College London, depending on the projects you have selected.

  • If your three preferred projects include one or more from King’s College London, then you should make an application to King’s via the King’s Apply Portal.
  • If your three preferred projects include one or more from Imperial College London, then you should make an application to Imperial via the admissions portal

Therefore, if your three preferred projects include projects from both King’s College London and Imperial College London, you should make an application to each institution. If you are proposing your own project then we encourage you to make applications to both institutions, since this will allow greater flexibility in identifying potential supervisors. 

Applicants may contact a prospective PhD supervisor to informally discuss their ideas before submitting an application, but should bear in mind that funding decisions will only be made after the applications have been received and processed by both King’s College London and Imperial College London, and by the Centre admissions team.

Please follow carefully the instructions below on how to apply, failure to do so may result in your application not being considered for the Centre. To ensure your application is complete and considered for the Centre read the application checklist below after you have completed your application.

To submit a complete an application you must:
  1. Apply to the relevant institution/s according to your preferred projects (and so if you have included projects from each institution then you will need to make an application to each institution). Note that supporting documentation such as transcripts can be submitted at a later date, but your application, research proposal and referee details must be received by the application submission deadline.
  2. Complete a STAI CDT Application Information Form 2020/21
Application Timeline

Applications are clsoed for September 2020 entry. The Centre will be considering applications in several rounds, until the Centre places have all been filled.

ROUND

A

B

C

D

E

F

Application Deadline

8 Nov 2019

10 Jan 2020

2 March 2020

20 April 2020

28 May 2020

3 July

Notification Expected

Jan 2019

March 2020

May 2020

July 2020

July 2020

Aug 2020

 

* Please note that later application rounds will only be held if there are still Centre places remaining for September 2020 entry. Once all Centre places have been filled, applications for September 2020 entry will close.

*Please note that the Centre does not have funding available for any further international students to join our Centre in September 2020.

Application Checklist

Please check that you have completed all of the following steps correctly.

1. Submit a PhD application to the relevant institution/s

  • If your preferred projects are all from King’s College London:
    Make an application to King’s College London, following carefully the instructions given here.
  • If your preferred projects are all from Imperial College London:
    Make an application to Imperial College London, following carefully the instructions given here.

     

  • If your preferred projects include projects from both King’s College London and Imperial College London:
    Make one application to King’s College London and one application to Imperial College London, following carefully the instructions given here and here.

2. Complete an STAI Centre Application Information Form

What happens next

Once you submit your complete Centre application it will be considered by the Centre selection committee. If you meet the eligibility requirements, your application will be discussed in next selection panel and you may be contacted by some supervisors of your preferred projects to conduct interviews.

Any questions relating to the Centre should be sent to stai-cdt@kcl.ac.uk. Note that this email address is not monitored outside of working hours, so any questions relating to an application should be sent well in advance of the application deadline.

Available Projects

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  • Abstract Interpretation for Safe Machine Learning

    Project ID: STAI-CDT-2020-IC-7
    Themes: AI Planning, Verification
    Supervisor: Sergio Maffeis

    Machine learning (ML) techniques such as Support Vector Machines, Random Forests and Neural Networks are being applied with great success to a wide range of complex and sometimes safety-critical tasks. Recent research in...

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  • Monitoring Compliance with Dynamic Norms under Uncertainty

    Project ID: STAI-CDT-2020-KCL-27
    Themes: AI Provenance, Norms
    Supervisor: Natalia Criado

    This project will develop the first norm monitor capable of checking compliance with dynamic and adaptable norms on the basis of incomplete and uncertain observations. Most of existing proposals on norm compliance...

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  • Learning Behavioural Norms for Autonomous System

    Project ID: STAI-CDT-2020-IC-13
    Themes: Norms
    Supervisor: Fariba Sadri

    This project focuses on the design and implementation of human interpretable intelligent autonomous systems. In particular the project will focus on developing and combining the following concepts and functionalities: •...

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  • Interactive explanations by argumentation

    Project ID: STAI-CDT-2020-IC-15
    Themes: Argumentation
    Supervisor: Francesca Toni

    Today’s AI landscape is permeated by plentiful data and dominated by powerful methods with the potential to impact a wide range of human sectors, including healthcare and the practice of law. Yet, this potential is...

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  • Explanation-empowered feedback via argumentation

    Project ID: STAI-CDT-2020-IC-16
    Themes: Argumentation
    Supervisor: Francesca Toni

    Today’s AI landscape is permeated by plentiful data and dominated by powerful methods with the potential to impact a wide range of human sectors, including healthcare and the practice of law. Yet, this potential is...

    Read more

  • A model-based verification for safe and trusted concurrent robotics systems

    Project ID: STAI-CDT-2020-IC-21
    Themes: AI Planning, Logic, Verification
    Supervisor: Nobuko Yoshida

    SUMMARY Robotics applications involve programming concurrent components synchronising through messages while simultaneously executing motion actions that control the state of the physical world. Today, these applications...

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  • A Novel Model-driven AI Paradigm for Intrusion Detection

    Project ID: STAI-CDT-2020-KCL-26
    Themes: AI Planning, Logic, Verification
    Supervisor: Fabio Pierazzi

    Intrusion Detection Systems (IDSs) are commonly deployed in networks and hosts to identify malicious activities representing misuse of computer systems. The numbers and types of attacks have been constantly increasing, and...

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  • Probabilistic Abstract Interpretation of Deep Neural Networks

    Project ID: STAI-CDT-2020-IC-30
    Themes: AI Planning, Verification
    Supervisor: Herbert Wiklicky

    The extraction of (symbolic) rules which describe the operation of (deep) neural networks which have been trained to perform a certain task is central to explaining their inner workings in order to judge their correctness,...

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  • Verifying Emergence Properties of Robotic Swarms

    Project ID: STAI-CDT-2020-IC-31
    Themes: AI Planning, Logic, Verification
    Supervisor: Alessio Lomuscio

    The effective development and deployment of single-robot systems is increasingly shown to be problematic in a variety of application domains including search and rescue, remote exploration, de-mining, etc. These and other...

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  • Discrete-continuous hybrid planning for adaptive cyber-physical systems

    Project ID: STAI-CDT-2020-IC-35
    Themes: AI Planning, Verification
    Supervisor: Antonio Filieri

    Adaptive cyber-physical systems rely on the composition and coordinated interaction of different decision-making procedures. Cyber components capabilities and semantics are usually captured by operational models (such as...

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  • Argumentation-based Interactive Explainable Scheduling

    Project ID: STAI-CDT-2020-IC-40
    Themes: Argumentation
    Supervisor: Ruth Misener

    AI is continuing to make progress in many settings, fuelled by data availability and computational power, but it is widely acknowledged that it cannot fully benefit society without addressing its widespread inability to...

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  • Digital twins for the verification of learning and adaptive software

    Project ID: STAI-CDT-2020-IC-41
    Themes: AI Planning, Verification
    Supervisor: Antonio Filieri

    Learning and decision-making AI components are gaining popularity as enablers of modern adaptive software. Common uses include, for example, the classification or regression of incoming data (e.g., face recognition), the...

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  • Neural-symbolic learning: a solution for generalisable and explainable AI

    Project ID: STAI-CDT-2020-IC-43
    Themes: AI Planning, Logic
    Supervisor: Alessandra Russo

    This research proposal focuses on developing a novel hybrid neural-symbolic learning approach that combines the capabilities of deep learning methods in extracting features from unstructured data with the ability of...

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  • Explanations for predictions by artificial neural networks by mining argumentative abstractions

    Project ID: STAI-CDT-2020-IC-44
    Themes: Argumentation
    Supervisor: Francesca Toni

    It is well-known that there are serious issues with opaque methods in AI, including artificial neural networks (ANNs), when these are used to support human decision-making. As a consequence considerable efforts are being...

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  • Correct-by-construction domain-specific AI planners

    Project ID: STAI-CDT-2020-KCL-10
    Themes: AI Planning, Verification
    Supervisor: Steffen Zschaler

    When using complex algorithms to make decisions within autonomous systems, the weak link is the abstract model used by the algorithms: any errors in the model may lead to unanticipated behaviour potentially risking...

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  • Trusted test suites for safe agent-based simulations

    Project ID: STAI-CDT-2020-KCL-11
    Themes: AI Planning, Verification
    Supervisor: Steffen Zschaler

    Agent-based models (ABMs) are an AI technique to help improve our understanding of complex real-world interactions and their ”emergent behaviour”. ABMs are used to develop and test theories or to explore how...

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  • Logical English

    Project ID: STAI-CDT-2020-IC-12
    Themes: Logic
    Supervisor: Fariba Sadri

    Computer programs today are written in machine-oriented languages, which are not intelligible without computer training. As a consequence, many of the people who are affected by computer applications have little...

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  • AI-inspired Logic-based Methods for the Verification of Security Protocols

    Project ID: STAI-CDT-2020-IC-36
    Themes: Logic, Norms, Verification
    Supervisor: Francesco Belardinelli

    The security and trustworthiness of AI systems poses a number of challenges related to the complexity of the systems at hand. Indeed, the design and development of security features calls for a careful modelling of the...

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