Research Associate in Catchment Modelling

at  University of Bristol

YOU SHOULD APPLY IF

• You have a good honours degree (or equivalent) and a relevant postgraduate research degree in hydrology.
• A strong understanding and experience of hydrological modelling (essential) and water quality (desirable).
• Strong analytical and coding skills within a package such as MATLAB, R, Python or FORTRAN.
• Experience of writing up results for publication in leading international peer-reviewed journals.
• Ability and enthusiasm to engage with stakeholders and partners across the water sector.

THE ROLE

The School of Civil, Aerospace and Design Engineering are looking to appoint a Research Associate for a 3-year position to develop hydrological models utilising smart water pollution data to improve predictive capacity at river basin scale. The Research Associate will be working as part of an interdisciplinary team of hydrologists, engineers, biogeochemists and ecohydrologists as part of the NERC Large Grant SMARTWATER ‘Diagnosing controls of hot spots and hot moments of water pollution: leveraging smart sensor networks and real-time data for process understanding’. This post presents an exciting opportunity to work on a global water challenge with an energetic interdisciplinary team and high potential for impact. There will be a strong focus on career development for the successful candidate with opportunities and funding available for training, placements with project partners and international research visits through our US partners at NorthWestern University.

WHAT WILL YOU BE DOING?

The primary activity of the successful applicant will be to develop hydrological models of SMARTWATER study sites at reach- to catchment-scale to identify broad-scale and long-term baseline conditions and extremes, including climate and regional environmental change. The outputs from these hydrological models will be used as boundary conditions for a suite of water quality models and a set of data-informed biogeochemical modelling toolboxes. The successful applicant will then combine these outputs in an over-arching modelling framework that will provide a pathway to large-scale pollution risk assessment.