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Applications for September 2021 entry will open in October 2020. 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.

Register for our Information Session - 2 November 2020

Join us for an information session to find out more about the Centre!

Date: Monday 2 November, 2020

Time: 10:00 – 11:30am

Register: via Eventbrite

Our Centre offers an exciting opportunity to develop your skills in one of the fastest growing research areas. A recent UK government report estimated that AI technologies could add £630 billion to the UK economy by 2035, but we need skilled individuals who can address growing concerns about the potential dangers of AI.

Register for our online information session to find out more about our programme and how to apply. Joining details are detailed on all registration confirmations under ‘additional information’.

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.  

UKRI are opening up UKRI studentships to home and international students from the 2021/22 academic year, to include a stipend and fees at the home level. However, there is a limit on the proportion of international students to 30 percent of the total cohort.

The information here is intended to summarise UKRI guidance on eligibility and has been updated in line with UKRI announcements

Home Students

Home students will be eligible for a full UKRI award, including fees and stipend, if they satisfy UKRI criteria, including residency requirements. To be classed as a Home student, candidates must meet the following criteria:

  •  be a UK National (meeting residency requirements), or
  •  have settled status, or
  •  have pre-settled status (meeting residency requirements), or
  •  have indefinite leave to remain or enter.

If a candidate does not meet the criteria above, they will be classed as an International student.

International students

International students will be eligible for full UKRI-funded studentships, including fees (at the home level) and stipend, from the start of the 2021/22 academic year, UK Research and Innovation has announced. Studentships for international students will be limited in number and competitive, and we encourage strong international candidates to apply.

EU Students 

Following the written statement by The Minister of State for Universities, EU, other EEA and Swiss nationals will no longer be eligible for home fee status from the academic year starting in August 2021. It will not affect EU, other EEA and Swiss nationals benefitting from Citizens’ Rights under the EU Withdrawal Agreement, EEA EFTA Separation Agreement or Swiss Citizens’ Rights Agreement respectively. It will also not apply to Irish nationals living in the UK and Ireland whose right to study and to access benefits and services will be preserved under the Common Travel Area arrangement.

Students living within the EU who do not meet eligibility requirements for Home Fee status will need to submit applications as international students in line with the UKRI announcement

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 2021 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. All candidates must complete a STAI Centre Application Information Form 2021/22 – failure to complete this form may result in your application not being considered for the Centre. 
Application Timeline

.Applications for September 2021 entry will open in October 2020. The Centre will be considering applications in several rounds, until the Centre places have all been filled.

ROUND

A

B

C

Application Deadline

22 November 2020

21 March 2021

13 June 2021

Notification Expected

February 2021

May 2021

July 2021

* Please note that at King’s, the Admissions Cycle for October 2021 entry will open on 26 October 2020.  You will not be able to submit an application until this date.

* Please note that later application rounds will only be held if there are still Centre places remaining for September 2021 entry. Once all Centre places have been filled, applications for September 2021 entry will close.

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. All applicants should also complete an STAI Centre Application Information Form – failure to complete this form may result in your application not being considered for the Centre. 

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.

Frequently Asked Questions - Studentship Interviews

 Where and when will interviews take place?

You can follow our expected timelines for recruitment activity by viewing our Application Timeline . Following submission of an application, shortlisted candidates will be invited to attend an interview, at either King’s College London or Imperial College London, (or virtually) with the supervisors of the project for which you have made an application (or with the supervisor identified as being a good fit for your proposed project) and a supporting panel of fellow academics. The supervisors will find a date and time that is mutually convenient with you for an interview to take place.

What can I expect from the interview?

Interviews typically take up to one hour and you will be asked questions so that the academics can find out more about you, your research interest and your skill set. It is likely that you will be asked questions around the following areas:

  • Your academic background and other relevant experience to the PhD project;
  • your suitability in relation to the Centre’s research aims;
  • your suitability in relation to the Centre model, which adopts a cohort-based approach and an integrated training programme;
  • your technical aptitude for the Centre (and this may involve reading scientific papers and solving problems);
  • your specific research interests;
  • your motivations for doing a PhD; and
  • your prior knowledge of AI and related areas.

Supervisors may ask you to carry out a specific form of assessment such as (but not limited to) reviewing a paper, preparing a presentation, or completing a technical test. A supervisor may also ask you to prepare something specific to their own research agenda (particularly if being interviewed by a supervisor whose project is the second or third choice in your application).

Following an initial interview, further interviews may be arranged as a follow-up if required by the project supervisors or by the Centre Directors.

You will also be given the opportunity to ask questions about the Centre training programme and any other element of the PhD project or institution at which you (and your PhD project) will be hosted.

What should I wear to an interview?

We want you to be comfortable in your interview so feel free to dress as you wish. It is unlikely that the academics leading the interview will be wearing formal office wear so don’t feel pressured to do so. We want you to feel relaxed so you can perform at your best.

Does the Centre financially reimburse candidates for attending an interview? 

The Centre is committed to ensuring being inclusive. We will reimburse up to £250 towards any additional costs (for example for care of a dependent child or adult; or for a candidate’s travel to an interview) that are incurred because of attending an interview for a studentship.

To discuss the process for reimbursement, please contact the Centre Manager via stai-cdt@kclac.uk once you have been invited to interview for a studentship.

 

Frequently Asked Questions - Post-Interviews

When will I find out about the outcome of my application?

Please have a look at the Application Timeline for the date by which you will be informed via email about the outcome of your application in the particular round in which you applied. We may occasionally need to defer decisions about your application, in which case you will be contacted by email and notified of the delay by the original deadline as detailed in the Application Timeline.

Note that we are unable to offer individual feedback on written applications, but candidates who are interviewed can request feedback from their interview by contacting stai-cdt@kcl.ac.uk; it is at the panel’s discretion to provide feedback to candidates.

I have been offered a studentship, what happens next?

If you are offered a place, you will first receive an offer of funding from the Centre Office, and you will need to accept this via email by a specific deadline detailed in the email. Following acceptance of the studentship funding, the King’s Apply Portal or Imperial Application Portal will be updated, and you will receive an offer letter from the relevant institution’s Admissions Team. The offer you receive will be an offer of a place on this specific programme. It is important for candidates to accept the offer made via the institution’s admissions portal.

You must therefore accept:

  • the offer of funding from the centre office; and
  • the offer of a place from King’s College London or Imperial College London via the Admissions Team of the institution at which you will be registered for your PhD.

Can I keep in touch before joining the Centre?

The Centre will send regular communications when you accept a studentship with us through to when you join us at our Induction in late September/early October. The Centre Manager will send paperwork over the summer months to you to complete before joining the Centre, and King’s or Imperial (depending on the institution at which you are accepted) will send you enrolment information from August. It is recommended that you keep in touch your supervisor and the Centre Office (stai-cdt@kcl.ac.uk) and send along any queries you have after accepting a place on the programme.

When is Induction?

We will confirm the date of our Centre Induction event in mid to late August (and this is distinct from, and additional to, any induction from the host department and/or institution). It is most likely to take place in the first week of October, and you will meet the Centre Team, Centre Directors, and some of our current students.

Available Projects

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  • A framework for verifying the safety and trustworthiness of AI systems

    Project ID: STAI-CDT-2021-KCL-1
    Themes: Argumentation
    Supervisor: Oana Cocarascu

    AI systems are increasingly used to aid human-decision making. Whilst AI systems have seen successes in a variety of tasks achieving highly-accurate results, oftentimes these systems tend to lack explainability and...

    Read more

  • Discrete-continuous hybrid planning for adaptive systems

    Project ID: STAI-CDT-2021-IC-15
    Themes: AI Planning, Verification
    Supervisor: Antonio Filieri

    Adaptive cyber-physical systems rely on the composition and coordinated interaction of different decision-making procedures, each typically realized with specific AI methods. Cyber components capabilities and semantics are...

    Read more

  • Debating Ethics: Using Natural Language Datasets to Support Human and AI debate

    Project ID: STAI-CDT-2021-KCL-2
    Themes: Argumentation
    Supervisor: Oana Cocarascu

    Artificial intelligence (AI) algorithms, including machine learning and deep learning techniques, have been applied with success to a plethora of natural language datasets and tasks, including argumentative text. The goal...

    Read more

  • Model Checking Agents that Learn

    Project ID: STAI-CDT-2021-IC-3
    Themes: AI Planning, Verification
    Supervisor: Francesco Belardinelli

    In Reinforcement Learning (RL) autonomous agents have typically to choose their actions in order to maximise some notion of cumulative reward [1]. Tools and techniques for RL have been applied successfully to domain as...

    Read more

  • Towards Trusted Epidemic Simulation

    Project ID: STAI-CDT-2021-IC-4
    Themes: Verification
    Supervisor: Wayne Luk

    Agent-based models (ABMs) are powerful methods to describe the spread of epidemics. An ABM treats each susceptible individual as an agent in a simulated world. The simulation algorithm of the model tracks the health status...

    Read more

  • Data-Driven and Explainable Discrete Optimization for Effective Transportation in Healthcare

    Project ID: STAI-CDT-2021-KCL-3
    Themes: AI Planning, Argumentation, Scheduling
    Supervisor: Dimitrios Letsios

    This project aims to contribute to the development of safe and trusted, artificially intelligent transportation in healthcare. The London Ambulance Service (LAS) operates more than 1100 ambulances to respond to medical...

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  • Enhancing Scale and Performance of Safe and Trusted Multi-Agent Planning

    Project ID: STAI-CDT-2021-IC-5
    Themes: AI Planning
    Supervisor: Wayne Luk

    Cooperative Multi-Agent Planning (MAP) is a topic in symbolic artificial intelligence (AI). In a cooperative MAP system, multiple agents collaborate to achieve a common goal. A cooperative MAP solver produces...

    Read more

  • Verifying Safety and Reliability of Robotic Swarms

    Project ID: STAI-CDT-2021-IC-6
    Themes: Logic, Verification
    Supervisor: Alessio Lomuscio

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

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  • Verification of AI-based perception systems

    Project ID: STAI-CDT-2021-IC-7
    Themes: Logic, Verification
    Supervisor: Alessio Lomuscio

    State-of-the-art present perception systems, including those based on Lidar or cameras, are increasingly being used in a range of critical applications including security and autonomous vehicles. While the present deep...

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  • A normative multi-agent framework to ensure resilience of autonomous vehicles’ AI algorithms against adversarial machine learning attacks.

    Project ID: STAI-CDT-2021-IC-1
    Themes: Norms
    Supervisor: Soteris Demetriou

    An increasing number of depth sensors and surrounding-aware cameras are being installed in the new generation of cars. For example, Tesla Motors uses a forward radar, a front-facing camera, and multiple ultrasonic sensors...

    Read more

  • Neural-symbolic Reinforcement Learning.

    Project ID: STAI-CDT-2021-IC-2
    Themes: AI Planning, Logic
    Supervisor: Alessandra Russo

    Recent advances in deep reinforcement learning (DRL) have allowed computer programs to beat humans at complex games like Chess or Go years before the original projections. However, the SOTA in DRL misses out on some of the...

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  • Safe Rational Interactions in Data-driven Control

    Project ID: STAI-CDT-2021-IC-8
    Themes: AI Planning, Logic, Verification
    Supervisor: Alessio Lomuscio

    In autonomous and multi-agent systems players are normally assumed rational and cooperating or competing in groups to achieve their overall objectives. Useful methods to study the resulting interactions come from game...

    Read more

  • Verification of neural-symbolic agent-based systems

    Project ID: STAI-CDT-2021-IC-9
    Themes: Logic, Verification
    Supervisor: Alessio Lomuscio

    Considerable work has been carried out in the past two decades on Verification of Multi-Agent Systems. Various methods based on binary-decision diagrams, bounded model checking, abstraction, symmetry reduction have been...

    Read more

  • Abstract Interpretation for Safe Machine Learning

    Project ID: STAI-CDT-2021-IC-10
    Themes: Logic, 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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  • Argumentation-based Interactive Explainable Scheduling

    Project ID: STAI-CDT-2021-IC-11
    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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  • Learning Behavioural Norms for Autonomous System

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

    Incorporation decision making, for example combining preferences and prospection Concrete applications can be autonomous vehicles, health care or smart contracts. Prospective reasoning allows hypothetical what-if scenarios...

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  • Digital twins for the verification of learning and adaptive software

    Project ID: STAI-CDT-2021-IC-13
    Themes: 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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  • Correct-by-construction domain-specific AI planners

    Project ID: STAI-CDT-2021-KCL-4
    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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  • Monitoring Compliance with Dynamic Norms under Uncertainty

    Project ID: STAI-CDT-2021-KCL-5
    Themes: 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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  • A Novel Model-driven AI Paradigm for Intrusion Detection

    Project ID: STAI-CDT-2021-KCL-6
    Themes: Logic, Verification
    Supervisor: Fabio Pierazzi

    This project aims to investigate, design and develop new model-driven methods for AI-based network intrusion detection systems. The emphasis is on designing an AI model that is able to verify and explain its safety...

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  • Probabilistic Abstract Interpretation of Deep Neural Networks

    Project ID: STAI-CDT-2021-IC-14
    Themes: 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...

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  • Trustworthy AI for DNA Sequencing

    Project ID: STAI-CDT-2021-IC-16
    Themes: Logic, Provenance
    Supervisor: Thomas Heinis

    DNA sequencing is becoming ever more important for medical applications, be it for predictive medicine or precision/personalised medicine. At the same time, DNA sequencing is starting to use AI to map signals (from the...

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  • Explainable AI by defeasible rules

    Project ID: STAI-CDT-2021-IC-17
    Themes: Argumentation, Logic
    Supervisor: Francesca Toni

    The field of explainable AI (XAI) is a particularly active area of research at the moment whose goal is to provide transparency to the decisions of traditionally more opaque machine learning techniques. Being able to assess...

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  • Hypothesis Knowledge Graphs

    Project ID: STAI-CDT-2021-KCL-7
    Themes: AI Provenance, Logic
    Supervisor: Albert Meroño Peñuela

    Generating hypotheses is a fundamental step in the scientific method, but also increasingly challenging due to the ever-growing observational data from which hypotheses are derived. Papers are published at an unmanageable...

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  • Trusted Test Suites for Safe Agent-Based Simulations

    Project ID: STAI-CDT-2021-KCL-8
    Themes: 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 behaviours”. ABMs are used to develop and test theories or to explore how interventions...

    Read more