Research Fellow in Advanced Semiconductor Device Modelling

The Methodist Church in Britain; London Borough of Southwark; On-site; GBP 42,000 - 56,000; Full time

Job summary

The University of Surrey invites applications for a Research Fellow in the Research & Teaching area, working on the EPSRC project EP/Y000196/1. The role focuses on building and validating simulation and predictive models for source-gated and multimodal transistors, combining computational work with experimental data.

Fixed-term until July 2027, with possible national/international travel, and a PhD with TCAD/AI modelling expertise required.

Qualifications

• PhD in Electronic Engineering, Semiconductor Device Physics, computational or numerical modelling, or a closely related discipline.
• Demonstrable expertise in high-fidelity TCAD, compact modelling, or advanced numerical or AI-assisted modelling of semiconductor devices, supported by publicly verifiable technical outputs.

Responsibilities

• Develop and validate predictive models of SGT and MMT devices using TCAD, compact modelling, surrogate modelling and physics-informed machine learning
• Fit and validate models against measured device data
• Work closely with the experimental team to incorporate device physics and manufacturing effects
• Use models to inform device and circuit design
• Produce publications, reusable models and simulation frameworks
• Maintain appropriate documentation
• Present findings at conferences and workshops
• Contribute to student mentoring
• Contribute to research proposals, external collaborations and international dissemination

Skills

TCAD modelling

Compact modelling

AI-assisted modelling

Numerical modelling

Education

PhD in Electronic Engineering

Tools

TCAD software

Surrogate modelling

Job description

This Research Fellow post sits within the University of Surrey's Research & Teaching area, working on EPSRC project EP/Y000196/1 under the principal investigator. Fixed-term until July 2027, the role centres on building and validating simulation and predictive models for source-gated and multimodal transistors. The work is mainly computational but stays tied to experimental device data, with possible national or international travel. A PhD and proven expertise in TCAD, compact modelling or AI-assisted device modelling decide fit.

What the job involves

• Develop and validate predictive models of SGT and MMT devices using TCAD, compact modelling, surrogate modelling and physics-informed machine learning
• Fit and validate models against measured device data
• Work closely with the experimental team to incorporate device physics and manufacturing effects
• Use models to inform device and circuit design
• Produce publications, reusable models and simulation frameworks
• Maintain appropriate documentation
• Present findings at conferences and workshops
• Contribute to student mentoring
• Contribute to research proposals, external collaborations and international dissemination

Qualifications

• PhD in Electronic Engineering, Semiconductor Device Physics, computational or numerical modelling, or a closely related discipline

Experience

• Demonstrable expertise in high-fidelity TCAD, compact modelling, or advanced numerical or AI-assisted modelling of semiconductor devices, supported by publicly verifiable technical outputs

Skills & knowledge

• Academic judgement in selecting and developing modelling approaches
• Critical interpretation of results
• Working with experimental data so models stay physically meaningful and grounded in measured behaviour