Two Fully Funded PhD Positions in Optical Neural Networks & AI Hardware

University of Sussex

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Vacancy

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Description

It is formally announced that applications are being invited for two fully funded doctoral research positions within the School of Engineering at the University of Sussex. These prestigious studentships offer an exceptional opportunity for ambitious researchers to join a leading research group under the supervision of Dr. Leila Yousefi. The positions provide full tuition coverage and a competitive stipend, enabling selected candidates to focus entirely on high-impact research in next-generation computing technologies. Students will work within an internationally recognized team specializing in optical computing, photonic systems, and advanced signal processing, contributing to innovative projects that address emerging challenges in future computing architectures. The program offers access to state-of-the-art laboratories, cutting-edge equipment, and comprehensive academic and technical support. Candidates will benefit from regular academic seminars, research workshops, and professional development opportunities that strengthen critical skills in scientific writing, analysis, and project management. Ideal applicants will have strong academic backgrounds in engineering, physics, computer science, or related fields, along with a commitment to research excellence and problem-solving. The University of Sussex provides a dynamic, inclusive, and research-intensive environment that fosters creativity and innovation. These studentships prepare graduates for impactful careers in academia, research institutions, and high-tech industries worldwide. Interested candidates are encouraged to apply promptly due to the highly competitive selection process. 

Responsibilities

Research Scope and Objectives

The core research mandate for these positions is centered on “Developing Optical Neural Networks for Next-Generation AI Systems.” The project aims to push the boundaries of computational performance by integrating principles from Electromagnetics, Photonics, and Artificial Intelligence. As AI workloads grow beyond the limits of traditional electronic hardware, this research focuses on creating innovative, light-based computing architectures that deliver unprecedented speed, efficiency, and scalability.

Research Scope:

• Investigate the fundamental principles of optical signal propagation and their application in neural network architectures.
• Explore the use of photonic components such as waveguides, modulators, and optical interference units for computing operations.
• Develop mathematical models and simulations to design, optimize, and validate optical neural network structures.
• Study the interaction between electromagnetic fields and photonic devices to enhance computational accuracy and stability.
• Examine energy consumption profiles of optical systems compared to conventional electronic hardware.
• Analyze system-level performance metrics, including speed, latency, throughput, and scalability in optical AI frameworks.
• Research hardware–software co-design strategies to integrate optical processing with existing AI algorithms.
• Evaluate the feasibility of hybrid architectures combining optical and electronic components for improved performance.

Research Objectives:

• Create highly efficient optical neural network prototypes capable of outperforming electronic counterparts in speed and energy use.
• Reduce computational bottlenecks in AI training and inference by leveraging the parallelism inherent in optical systems.
• Design novel photonic circuits tailored for AI operations such as convolution, matrix multiplication, and nonlinear activation.
• Develop new methods for encoding and manipulating data using light to increase processing capacity.
• Improve the reliability and precision of optical computing through advanced materials, device engineering, and machine-learning–driven optimization.
• Demonstrate proof-of-concept systems that validate the practicality of next-generation optical AI technologies.
• Contribute to foundational research that supports the future development of commercial-scale optical computing platforms. 

Qualification

Candidate Eligibility and Requirements

To be considered for these highly competitive doctoral positions, applicants must demonstrate strong academic preparation, technical expertise, and clear alignment with the research vision of the program. The following criteria outline the essential qualifications expected from all prospective candidates:

1. Academic Qualification: Applicants must hold a Master’s degree (MSc or MPhil) in Electrical Engineering or a closely related discipline. The degree should reflect rigorous training in core engineering principles and advanced coursework relevant to the research area.
2. Technical Specialization: Candidates are required to possess a deep theoretical understanding and practical experience in Electromagnetics and Photonics. Familiarity with optical devices, electromagnetic wave theory, photonic materials, and related computational tools will be highly advantageous.
3. Academic Excellence: A proven record of outstanding academic achievement is essential. Applicants should demonstrate high GPAs in both undergraduate and postgraduate studies, strong performance in advanced technical courses, and evidence of consistent academic dedication.
4. Research Alignment: Applicants must show a clear and compelling interest in hardware acceleration for AI, optical neural networks, and next-generation computing architectures. Prior exposure to research, thesis work, publications, or projects in related fields will strengthen the application.
5. Analytical and Problem-Solving Ability: Strong mathematical skills, the ability to analyze complex systems, and a capacity for innovative problem-solving are vital for success in this research domain.
6. Research Experience (Preferred): Previous involvement in laboratory work, simulation-based research, or computational modelling in Electromagnetics, Photonics, or AI hardware is considered an added advantage.
7. Technical Tools Competency: Familiarity with simulation platforms such as COMSOL, Lumerical, CST Studio Suite, MATLAB, or Python is highly desirable and may be required for project execution.
8. Communication Skills: Strong written and verbal communication abilities are expected, particularly for preparing research reports, scientific publications, and academic presentations. 

Scholarship Schemes and Funding

Financial support for these doctoral roles is secured through two distinct and prestigious funding bodies. Full tuition and stipends are provided to successful applicants. Detailed terms for each specific stream can be reviewed via the following portals:

• EPSRC Science and Engineering Studentships (2026 Intake): Comprehensive funding provided by the Engineering and Physical Sciences Research Council. View EPSRC Scheme Details
• Sussex AI PhD Studentships: Specialized funding dedicated to the advancement of Artificial Intelligence technologies. View Sussex AI Scheme Details 

Application and Contact Procedure

The application process for these positions is currently open. Preliminary matching and screening are being conducted directly by the lead supervisor.

• Submission Requirements: Interested candidates are requested to prepare a comprehensive Curriculum Vitae (CV) detailing academic history, publication records (if applicable), and technical skills.
• Contact Method: The CV and a brief expression of interest should be transmitted via email to Dr. Leila Yousefi.
• Email Address: l.yousefi@sussex.ac.uk 

Note: Applicants are strongly advised to review the specific eligibility requirements listed on the official EPSRC and Sussex AI links provided above before submission.