PhD Studentship: AI/ML for Embedded Systems

Overview

• Qualification type: PhD
• Subject area: Machine Learning, Artificial Intelligence, Embedded Systems.
• Location/Campus: College Lane campus, Hatfield, UK.
• Start date: 1 May 2023 or as soon as possible thereafter.
• Closing application date: 31 March 2024
• Duration: three years, full time

Project outline

As a Ph.D. researcher specializing in Artificial Intelligence / Machine Learning for Embedded Systems, you will play a pivotal role in advancing the state-of-the-art in AI on the edge. This position offers an exciting opportunity to engage in cutting-edge research and contribute to the development of innovative machine learning based implementations on hardware platforms, targeting at optimising the performance of the AI embedded systems on various applications.

In this research, you are expected to develop novel methods for the implementation of cutting edge machine learning and deep learning algorithms on embedded hardware platforms.

Key Responsibilities

• Conduct in-depth literature reviews and market analysis to identify current trends and challenges in this area of research.
• Design, simulate, and optimize machine learning based methods for implementation on embedded hardware platforms like MCUs, DSP, FPGAs..
• Collaborate with interdisciplinary teams, including engineers, data scientists, researchers, and industry partners, to validate and prototype innovative methodologies.
• Publish research findings in reputable journals and present results at conferences, contributing to patents and to the academic and scientific community.

Supervisors

• Principal supervisor: Dr Iosif Mporas
• Second supervisor: Dr Somayyeh Timarchi

Entry requirements

Essential

• A first or upper second-class degree (or equivalent) in a relevant discipline such as, electronic engineering, computer science, maths, etc.
• Knowledge in programming hardware boards (MCUs, DSP, FPGAs).
• Knowledge in machine learning and deep learning.
• Ability to implement specialised innovative ideas into code.
• Ability to work collaboratively and manage time independently to meet deadlines.
• Problem-solving skills and attention to detail.
• Excellent oral and written English communication skills, including the ability to communicate with clarity on complex information.
• excellent IT literacy.
• Applicants must be self-motivated.

Desirable

• A relevant master’s degree will be an advantage.
• Publications in high-impact international journals and conferences.
• Experience in embedded hardware systems and VHDL.
• Good knowledge of programming language Python preferably in Linux environment.
• Previous experience with state-of-the-art AI/ML software libraries (TensorFlow, Scikit-Learn, PyTorch, etc).

Eligibility

The studentship is open to UK/EU and international applicants.

How to Apply

Informal enquires can be made to Dr Iosif Mporas (i.mporas@herts.ac.uk), Director Research Centre Networks and Security.

Please download and complete an application form

In section 11 you must provide a comprehensive personal statement of up to 500 words describing your motivation to do research on this project at the University of Hertfordshire, and providing information on how you meet any of the essential or desirable requirements described above.

Please also send with your application form:

• A research proposal not exceeding 1 page.
• Two academic references.
• Copies of qualification certificates and transcripts.
• Certification of English language competence (minimum IELTS 6.5 or equivalent) for candidates for whom English is not their first language.

Your completed application should be emailed to the Doctoral College

Closing date for applications: 31 March 2024.

Interview dates: beginning of April 2024.

Expected studentship start date: 1 May 2024 (or as soon as possible thereafter).

Funding information

The award includes cover for UK home or international tuition fees and a stipend at standard UKRI rates. For 2023-2024 this is set at £18,622. The stipends usually increase annually in line with inflation. Applicants from outside the UK or EU are eligible.

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