Machine Learning Jobs in Exeter

• Exeter
• Entry level
• Contract

A PhD studentship developing neural networks within the MaLCOM machine learning framework to move mixed layer depth prediction from a statistical baseline to temporally resolved hourly forecasts. The researcher selects geographic test sites, temporal scales and oceanographic variables, using high-resolution in-situ and Earth observation data, with training in Python, AI and operational forecasting from Exeter, PML and the Met Office.

MaLCOM

• Exeter
• Entry level
• Contract

A PhD studentship investigating whether repeat photography, citizen science and machine learning can robustly monitor ecological change in intertidal habitats. The researcher combines field data collection, statistical analysis and image-based AI, validating methods against the 25-year MarClim time series across 100 UK rocky intertidal sites.

MarClim

• Exeter
• £21,805 pa
• Entry level
• Contract

Develops a multiscale Scientific Machine Learning digital-twin framework to predict thermal trajectories, torque capability and efficiency in low-speed, high-torque electric propulsion. Combines physics-informed neural networks, neural state-space models and Neural ODEs, validated through safety-constrained dynamometer experiments at the Centre for Future Clean Mobility and on-site work with a marine power-systems partner.

Neural Ordinary Differential Equations · Deep Neural Networks · Recurrent Neural Networks +1

• Exeter
• £21,805 pa
• Entry level
• Contract

Builds next-generation machine learning models to predict genetic interactions from large-scale perturb-seq data, evaluating graph neural networks and autoencoders for genome-wide scalability and cross-cancer generalisation. Works in a lab-in-the-loop cycle with AstraZeneca and Cancer Research Horizons FGC, who generate pancreatic cancer perturb-seq data to fine-tune the computational models. Purely computational, with high performance computing and industry-aligned experience.

Perturb-seq · DepMap · Project Score

• Exeter
• £21,805 pa
• Entry level
• Contract

An interdisciplinary PhD developing miniaturised, low-power sensing hardware co-designed with AI for monitoring wild animal behaviour, including individual recognition and automated quantification of responses. Systems are benchmarked in controlled conditions then validated on wild jackdaws and field sites in West Africa, spanning ecology, electronic engineering and data science.

Thermal Imaging · AI · Machine Learning

• Exeter
• On-site
• £21,805 pa
• Entry level
• Contract

A fully funded PhD studentship researching how small language models can become reliable agents for bounded business workflows, using harness optimisation and fine-tuning on traces from larger teacher models. The work measures reliability, cost, latency and data locality, and releases open tooling for UK SMEs, in collaboration with an industry research lab.

Large Language Models