Ocean Forecast Verification: AI-Driven Industry Placement

Met Office; Exeter; Híbrido; GBP 23.000 - 31.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Salary £27,170

Annual leave 27.5 days

Retail discounts

Descripción de la vacante

Met Office is offering a 12-month Year in Industry placement in Exeter, starting July 2027. You will work with the Ocean Forecast Verification team on building a prototype Agentic AI capability for operational ocean monitoring and event attribution.

The role includes collaboration with marine experts and hands-on development of AI-powered monitoring tools. The placement emphasizes training AI agents, QA and anomaly detection for forecasts, and presenting system status in natural language for end

Formación

• Pursuing a degree in a mathematical or physical science with an industrial placement year.
• Demonstrated interest in AI/ML and computing.
• Experience in programming or scientific computing tools such as Python, Fortran or MATLAB.
• Strong analytical and problem-solving abilities.
• Clear communication and collaborative teamwork skills.

Responsabilidades

• Develop an Agentic AI-driven monitoring workflow for marine forecasts.
• Train AI Agents to assess model outputs and highlight anomalies.
• Support quality assurance and anomaly detection for marine forecasts.
• Summarise system status in natural language for end users.

Conocimientos

Python

Fortran

MATLAB

AI/ML interest

Analytical thinking

Teamwork

Educación

Mathematical or Physical Science degree (with industrial placement year)

Herramientas

Python

Fortran

MATLAB

Descripción del empleo

Met Office is offering a 12-month Year in Industry placement in Exeter, starting July 2027. You will work with the Ocean Forecast Verification team on building a prototype Agentic AI capability for operational ocean monitoring and event attribution.

The role includes collaboration with marine experts and hands-on development of AI-powered monitoring tools. The placement emphasizes training AI agents, QA and anomaly detection for forecasts, and presenting system status in natural language for end