Validating, Monitoring and Explaining model decisions

We are recruiting new Doctoral Researchers to our EPSRC funded Doctoral Training Partnership (DTP) PhD studentships starting 1 October 2023. Applications are invited for the project Validating, Monitoring and Explaining model decisions

Successful applicants will receive an annual stipend (bursary) of approximately £19,668, including inner London weighting, plus payment of their full-time home tuition fees for a period of 42 months (3.5 years).

You should be eligible for home (UK) tuition fees there are a very limited number (no more than three) of studentships available to overseas applicants, including EU nationals, who meet the academic entry criteria including English Language proficiency.

You will join the internationally recognised researchers in the Department of Computer Science

The Project

As Machine Learning (AI) models underpin many of the decision tools these need to be monitored, validated and explainable for decisions to be trusted.

The aim of this research is to explore, develop and evaluate methods and interfaces to robustly validate, monitor and explain model decisions over time; to identify reasons for model performance drift, devise and evaluate guidelines to promote trust in model decisions over time.

Possible areas: health benchmarking models, credit risk models.

Please contact Dr Isabel Sassoon at isabel.sassoon@brunel.ac.uk for an informal discussion about the studentships.

Eligibility

Applicants will have or be expected to receive a first or upper-second class honours degree in an Engineering, Computer Science, Design, Mathematics, Physics or a similar discipline. A Postgraduate Masters degree is not required but may be an advantage.

Skills and Experience

Applicants will be required to demonstrate their knowledge applying AI, Machine Learning, or related (e.g., Natural Language Processing) techniques . Desirable: Software development, UX development experience running user studies.

You should be highly motivated, able to work independently as well as in a team, collaborate with others and have good communication skills.

How to apply

There are two stages of the application:

1.Applicants must submit the pre-application form via the following link by 16.00 on Friday 26th May 2023.

2.If you are shortlisted for the interview, you will be asked to email the following documentation in a single PDF file to cedps-studentships@brunel.ac.uk within 24hrs.

Your up-to-date CV;
Your Undergraduate degree certificate(s) and transcript(s) essential;
Your Postgraduate Masters degree certificate(s) and transcript(s) if applicable;
Your valid English Language qualification of IELTS 6.5 overall (minimum 6.0 in each section) or equivalent, if applicable;
Contact details for TWO referees, one of which can be an academic member of staff in the College.

Applicants should therefore ensure that they have all of this information in case they are shortlisted.

Interviews will take place in June 2023.

Meet the Supervisor(s)

Isabel Sassoon - Dr Isabel Sassoon is a Senior Lecturer in Computer Science at 明星八卦 University. Isabel was 明星八卦 Lead Investigator on IMMUNE (Immunity Passport Service Design) an UKRI Arts and Humanities Research Council funded project. IMMUNE's aim is to research the unintended consequences and risks related to immunity passports for COVID-19 with a view to inform their design in way that mitigates these. Before joining 明星八卦 Isabel was Research Associate on the CONSULT (Collaborative Mobile Decision Support for Managing Multiple Morbidities), an EPSRC funded project in the Department of Informatics in King’s College London. This project developed a collaborative mobile decision-support system to help patients suffering from chronic diseases to self-manage their treatment, by bringing together and reasoning with wellbeing sensor data, clinical guidelines and patient data. Prior to that Isabel was Teaching Fellow in the Department of Informatics in King’s College London, primarily on the Data Science MSc. Isabel's research interests are in data-driven automated reasoning, and its transparency and explainability. Her PhD research developed a computational argumentation based system to support the appropriate selection of statistical model given a research objective and available data. Her current research continues to explore how computational argumentation can assist in model explainability and trust. Prior to joining King's College London Isabel worked for more than 10 years as a data science consultant in industry, including 8 years in SAS UK. Isabel read Statistics, Operations Research and Economics at Tel Aviv University and received her Ph.D. in Informatics from King's College London. Isabel is a fellow of the Royal Statistical Society and Editorial Board Member of Real World Data Science,

Related Research Group(s)

Modelling and Simulation - Investigating how modelling and simulation can be supported by research into high-performance computing, e-infrastructures, cyberinfrastructures, cloud computing and web-based simulation.

AI Social and Digital Innovation - Social, economic and strategic effects of AI and associated technologies. Impact of AI and related technologies on societies, organisations and individuals.