Hydrological Data Scientist

UK Centre for Ecology & Hydrology
Wallingford, United Kingdom
Position Type: 
Full-Time
Organization Type: 
University/Academia/Research/Think tank
Experience Level: 
Not Specified
Degree Required: 
Advanced Degree (Master's or JD)

EXPIRED

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Research Associate, Hydrological Data Scientist
Full time (37 hours per week)
Band 7 - £25,150 - £26,500 (depending on skills and knowledge)
UKEH Wallingford, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire, OX10 8BB
Fixed term for 3 years
Closing date for applications is Sunday 17th January 2021
Interviews to be held on Tuesday 26th January 2021

Job Purpose

A three year training programme to for a Hydrological Data Scientist to advance our ability to apply machine learning, AI and other advanced statistical approaches to the analysis of complex hydro-climatic datasets to support water resources applications and the UKCEH’s wider environmental informatics activities.

Main Responsibilities

  • Provide data science input across a range of data-intensive hydrological projects in UKCEH.  
  • Work closely with other scientists, both within UKCEH and more widely, to deliver high quality datasets for use by a range of stakeholders. 
  • Assist in producing and managing large datasets (e.g. relational databases, netCDF files) 
  • Conduct complex analysis using R, python and software for data pipeline development (e.g. Kafka)
  • Producing outputs suitable for research journals and scientific reports.  

Over the 3 years you will gain skills in:

How to apply existing machine learning pipelines, using established toolkits and packages (e.g. pytorch, keras), for novel application in hydrology, and explore state-of-the-art methods to deal with new types data and to address emerging environmental problems. You will develop capabilities to support real-time monitoring & forecasting, climate risk assessment and water resources modelling in the UK and internationally.  Advanced skills in the application of advanced statistical and computational approaches (including AI/Machine Learning) within water science - for example, researching how such techniques can help improve data quality control and the analysis of complex hydro-climatic datasets.

Skills Criteria

Knowledge & Qualifications

  • Educated to Masters or PhD level in a scientific discipline with a heavily numerate / computing element, or  a graduate with directly relevant work experience
  • Keeps up to date with current thinking in the area of data science

Experience/Proven abilities related to the position

  • Excellent numeracy and previous statistical analysis experience
  • Experience of hydrological analysis
  • Experience managing and working with complex environmental datasets

Skills

  • Programming experience in Python or R
  • Able to work independently, communicating with
  • line management when appropriate
  • Able to develop complex analytical workflows
  • Able to clearly communicate arguments and complex concepts to peers in written and verbal form

Core Behaviours & Values

  • You will demonstrate a commitment to promote and adhere to UKCEH values of Excellence, Integrity and Teamwork.

Desirable skills

  • Experience in Machine learning

What we offer

To find out the benefits of working with UKCEH, please follow the link  below for a summary.  https://www.ceh.ac.uk/sites/default/files/UKCEH-Terms-and-Conditions-Summary.pdf 

About the Research Associate Programme

The initial appointment for Research Associates will normally be for a three-year term, however they are able to apply internally for permanent vacancies at any time. Subject to the Research Associate's performance and long term skills needs within their Science Area, appointments may be reviewed and considered for open ended positions. There is an expectation that RA will be appointed at the bottom of the salary scale and will automatically progress to the next pay point at the anniversary of their appointment.

How to Apply

To apply for this position, click the link below. As well as a CV, please provide a covering letter detailing why you may be suitable for the role.