Drainage Modeller

We have an exciting opening for drainage modeller to help us deliver on our expanding portfolio of UK and international research and consultancy projects.

Current projects within the Catchments and Drainage team include:

• Modelling the impacts of retrofitting Sustainable Drainage Systems (SuDS) in cities in Europe and the Caribbean as part of climate resilient planning strategies;
• Evaluating impacts of Combined Sewer Overflow (CSO) spills and urban runoff discharges;
• Governance of water company modelling and asset delivery strategies;
• Modelling and master planning drainage asset portfolios;
• Developing climate-adjusted rainfall time series and risk-based approaches to drainage design for flood and spill risk mitigation;
• Creating tools for the planning, evaluation and design of SuDS;
• Creating digital AI modelling solutions and applications;
• Developing industry good practice guidance.

 

The team sits within the wider Flood and Water Management Group. Across this Group, we have a wide variety of experts including in water resources, flood risk systems analyses, flood forecasting, international climate adaptation and resilience, statistical modelling, data visualisation and management, and the use of earth observation data.  Our work cuts across regulatory, government and private sector consultancy and research sectors – both in the UK and internationally, and we are continuously generating new knowledge, skills and tools through our ongoing programme of internally-funded research. Within your role, you would be interacting and developing solutions with staff in all of these fields, in order to win and deliver projects and support clients across the Group. 

The Group are recognised for our innovation.  We won the ‘Digital Excellence’ category at the Environment Agency’s Flood and Coast Excellence Awards 2024 with our Resilience and Innovation Northants (RAIN) platform for Northamptonshire Council (Home Page - RAIN). Our Intelligent Dam Safety Monitoring (DAMSAT) project won two awards at the New Civil Engineer Techfest Awards and  our Dengue forecasting MOdel Satellite-based System (D-MOSS) has won 9 different industry awards. We have recently been successful in securing Ofwat Innovation Funding for a national SuDS platform (with Southern Water) and for developing a Rainwater Management Platform (with Wessex Water).  We were also one of the ten finalists for the Manchester Prize for which we were funded to develop an AI sewer spill water quality impact tool.

About the role

We are looking for an enthusiastic and highly motivated individual with existing demonstrable drainage modelling expertise and skills in data analysis who can help us with the development of new ideas and solutions, alongside providing robust established support to our clients.

About you

You will be a recent graduate, or soon to graduate, with an interest in surface water and/or wastewater drainage modelling. Knowledge of InfoWorks ICM, GIS, coding, hydraulic modelling or data analysis gained through your degree, university projects, placements or internships would be advantageous. You will be interested in solving complex, data-intensive problems and have an understanding of the challenges and solutions associated with urban runoff. Importantly, you will be a collaborative team player with a willingness to learn and develop your technical skills.

You will have, or be expected to achieve, a Bachelor's degree in a relevant discipline. You will also have studied mathematics to A level (or equivalent) and be comfortable working with numerical and analytical data.

Further information

• Download a full job description and person specification.
• Salary: Competitive (depending on experience).
• This role will stay open until a suitable candidate is sourced.

Why choose us?

• Exceptional benefits: Enjoy a defined contribution pension scheme with a minimum 10% employer contribution (matched up to an additional 5%), 25 days of holiday plus bank holidays, life insurance, and health insurance providing dental/optical cash back.