Assistant Professor (Research Focussed)

Warwick; Coventry; Hybrid; GBP 48,000 - 58,000; Full time

Job summary

Warwick in Coventry invites applications for an Assistant Professor (Research Focused) in High Performance Computing, to contribute to the EPSRC-funded Accelerating Multilevel Monte Carlo on FPGAs project, led by Professor Gihan Mudalige.

The successful candidate will develop FPGA-based stochastic simulation software, collaborate with Oxford and AMD on hardware accelerators, and contribute to international research excellence in numerical methods and hardware acceleration.

Qualifications

• Experience in FPGA accelerator development and HPC.
• Background in numerical methods or scientific software development.
• Designing, implementing and optimising FPGA-based stochastic simulation software.
• Experience with stochastic differential equation models is a plus.
• Ability to collaborate across academic and industrial partnerships.

Responsibilities

• Lead development of FPGA-based stochastic simulation software.
• Design, implement and optimise FPGA accelerator solutions for HPC applications.
• Collaborate with internal and external partners (Oxford, AMD) on methodologies and tooling.

Skills

FPGA accelerator development

High-performance computing

Numerical computing

Scientific software development

High-level synthesis

Tools

FPGA tools

Job description

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Job Title: Assistant Professor (Research Focussed)

Reference: 472

Department: Computer Science

Fixed Term End Date: 30 September 2028

Hours: Full-time (1.0 FTE)

Full time Salary Range: £48,337.00- £57,666.00per annum

About the Role

Applications are invited for An Assistant Professor (Research Focused) (High Performance Computing) position on the EPSRC-funded Accelerating Multilevel Monte Carlo on FPGAs: A High-Performance Solution for Stochastic Simulations project, led by Professor Gihan Mudalige.

The project investigates the use of Field Programmable Gate Arrays (FPGAs) to accelerate computational intensive stochastic simulations. The research combines customised FPGA data-flow architectures, reduced-precision/fixed-point arithmetic and Multilevel Monte Carlo (MLMC) numerical methods to achieve high computational performance and energy efficiency while retaining the accuracy required by scientific applications.

The successful candidate will play a leading role in developing novel FPGA-based solutions for scientific computing and will contribute to internationally recognised research at the intersection of high-performance computing, numerical methods and hardware acceleration.

For details on the experience and skills required, please refer to the job description ( link here ).

About You

You will have experience in FPGA accelerator development and a strong background in high-performance computing, numerical methods or scientific software development. You will be responsible for designing, implementing and optimising FPGA-based stochastic simulation software, initially for stochastic differential equation models and subsequently for more advanced financial and biochemical applications.

You will work closely with collaborators at the University of Oxford, who are developing the associated mathematical accuracy and optimisation methodologies, and with AMD in relation to FPGA hardware and development tools.

We are particularly interested in candidates with expertise in FPGA accelerator development, high-level synthesis, numerical computing and high-performance software optimisation, together with the ability to work collaboratively across academic and industrial partnerships.

About the Department

The Department of Computer Science is proud of their diverse community of staff, students and visitors, and are committed to maintaining an excellent record in teaching and research by ensuring there is equality of opportunity for all, fostered in an environment of mutual respect and dignity.

The Department of Computer Science holds an Athena Swan – Silver Award. The award recognises advancement of gender equality: representation, progression and success for all.

For further information about The Department of Computer Science, please visit our website .