6 of 6 Physics Jobs in Edinburgh

and external stakeholders and work with the SeeByte CTO and other research staff to shape SeeBytes research strategy. Key Skills, Experience and Qualifications A strong academic background in mathematics, physics, engineering, or a related field (e.g., BSc/MSc/PhD). Solid understanding of statistics, linear algebra, probability, optimisation, and machine learning techniques. Experience with algorithm development, numerical methods More ❯

and external stakeholders and work with the SeeByte CTO and other research staff to shape SeeBytes research strategy. Key Skills, Experience and Qualifications A strong academic background in mathematics, physics, engineering, or a related field (e.g., BSc/MSc/PhD). Solid understanding of statistics, linear algebra, probability, optimisation, and machine learning techniques. Experience with algorithm development, numerical methods More ❯

the market What they're looking for: Equivalent track record of working in the following fields, or a PhD in: Engineering/Computer Science/Informatics/Maths/Physics Previous work with Optics/Imaging/Photonics and Digital/Electronic Systems Demonstrable background in Research/similar R&D roles, and ability to translate research results for technical More ❯

FPGA technologies from either Xilinx, Intel (Altera) or Microsemi (Actel) and their tools. - Degree (BSc, BEng, MEng, MSc, PhD, EngD) in Electrical & Electronic Engineering (preferable) or related science (e.g. Physics). SC clearance is essential to start in this position but a lapsed clearance or an exceptional candidate will be considered. Interviews are taking place over the next week so More ❯

vetting checks. Qualifications As a minimum requirement you'll be predicted to obtain, a 2.2 in your Bachelor's in Computing, computer science or IT networks related subject; Maths; Physics Start date (dd Month Year) 22nd June 2026 Length of contract 12 months More ❯

and Generative AI techniques in real-world projects, delivering innovative products to market You hold a degree in a technical or quantitative field (e.g., AI, computer science, engineering, mathematics, physics, or related discipline) with proven professional experience applying data science in commercial or research environments You possess strong analytical skills, demonstrate attention to detail, and excel at transforming data into … team environments while taking full ownership of your deliverables Desirable: Advanced ML Architectures : Experience with implementing specialised neural networks such as Graph Neural Networks (GNN) for modelling complex relationships, Physics-Informed Neural Networks (PINN) for incorporating domain knowledge, or Temporal Fusion Transformers (TFT) for advanced and interpretable forecasting LLM Specialisation : Hands-on experience with modern LLM training techniques including fine More ❯