Mathematical Modeller

at  Centre for Ecology Hydrology

Salary: £36,245 - £38,463
Hybrid working 50/50
Permanent, full-time (37 hours)
We will start reviewing applications from Monday, 13th May 2024. We reserve the right to close this advert early if we find the right candidate, so we encourage you to apply early.
UKCEH is looking for a Mathematical Modeller to join our 600+ strong team, contributing to scientific discovery and generating the data, insights and solutions that researchers, businesses and governments need to solve complex environmental challenges.
Working at UKCEH is rewarding. Our science makes a real difference, enabling people and the environment to prosper, and enriching society. We are the custodians of a wealth of environmental data, collected by UKCEH and its predecessors over the course of more than 60 years.

As a valued member of our team, you’ll get:

• 27 days annual leave, rising to 29 days after five years
• 10% pension contribution
• Enhanced maternity and paternity leave
• 24- hour, 365-day access to support with physical, mental, social, health or financial issues
• Flexible working opportunities

..
Join our dynamic
Hydro-Climate Risk Science Area
, where you’ll play key role in advancing flood estimation and hydrological risk methodologies within the Hydrological Forecasting Group! Your work will contribute to tackling critical research questions and policy needs aimed at enhancing flood risk management in the face of climate change.
You’ll be joining a leading independent, not-for-profit research institute that’s committed to recruiting talented people like you, progressing your career and giving you the support you need to thrive at UKCEH.

Your main responsibilities will include:

• Innovative modelling and statistical approaches for hydrological climate change impact analysis
• Developing next-generation Flood Estimation Handbook (FEH) methods for industry and policy makers
• Novel analysis of large hydrometeorological and climate datasets and modelling

Projects you’ll be working on:

• Exploiting and building upon a state-of-the-art archive of flood events as part of the

Hydro-JULES

NERC project,

• Modelling and analysing novel climatic and hydrological large ensemble model simulations as part of the

STORMS

project in the DAFNI Centre of Excellence,

• Updating industry standard methods for UK Flood Estimation including new techniques to model the spatial and temporal variability of extreme floods.

For the role of Mathematical Modeller, we’re looking for somebody with:

• A PhD in a mathematical or numerate science subject, or relevant post graduate experience
• A degree in a numerate discipline
• Proven ability of working with big data to develop a new understanding of physical or environmental processes/systems
• Experience in developing and applying a model of hydrological/environmental systems
• Evidence of applying statistical modelling and analysis, e.g. time-series analysis or machine learning.
• Proven experience of scientific programming in R or/and Python
• Experience with High Performance Computing or Linux batch processing
• Demonstrable understanding of the importance of data quality, data visualisation and method assumptions
• Hydrological science understanding or an interest in learning more

If we’ve just described you, we’d love to meet. Apply now.

Your main responsibilities will include:

• Innovative modelling and statistical approaches for hydrological climate change impact analysis
• Developing next-generation Flood Estimation Handbook (FEH) methods for industry and policy makers
• Novel analysis of large hydrometeorological and climate datasets and modellin

For the role of Mathematical Modeller, we’re looking for somebody with:

• A PhD in a mathematical or numerate science subject, or relevant post graduate experience
• A degree in a numerate discipline
• Proven ability of working with big data to develop a new understanding of physical or environmental processes/systems
• Experience in developing and applying a model of hydrological/environmental systems
• Evidence of applying statistical modelling and analysis, e.g. time-series analysis or machine learning.
• Proven experience of scientific programming in R or/and Python
• Experience with High Performance Computing or Linux batch processing
• Demonstrable understanding of the importance of data quality, data visualisation and method assumptions
• Hydrological science understanding or an interest in learning mor