High Resolution Unstructured Grid Modelling Scientist

PML hosts one of the largest and most active marine system modelling groups in the world (https://www.pml.ac.uk/science/Marine-Systems-Modelling). Our mission is to promote greater fundamental understanding of marine systems by developing and applying state-of-the-art computational models. These models simulate marine system functioning and its response to local and global pressures. We use this understanding to promote sustainable use of marine ecosystems, addressing many of the UN sustainable development goals and contributing to IPCC reporting. We take a “systems” approach, integrating oceanography, marine physics, chemistry, biology, and ecology across the water column, sediments and land and atmospheric interfaces. We integrate models with data from laboratory experiments, in situ and remotely sensed marine observations to test hypotheses, validate simulations, sustain monitoring, and improve forecasts. Our whole systems approach provides an unrivalled ability to understand the marine system and improve predictions of change in the ocean state, ecological functioning, and ecosystem services.

We are looking for a highly motivated and capable scientist with experience in computer modelling to join our dynamic team. The group focuses on developing and applying coupled biogeochemical-hydrodynamic high-resolution models primarily based on FVCOM to address a range of topics including land-coast interactions, renewable energy, pollution, and aquaculture including the development of operational forecasting systems. The position is suitable for candidates with a background in physics, computer modelling or oceanography with a keen interest in marine environmental issues.

Requirements

• Experience with designing and executing model implementations with unstructured grid models such as FVCOM, SCHISM or FESOM (essential)
• Experience with implementation of hydrodynamic models at high-resolution (sub-km scale)
• Knowledge of FORTRAN (essential), with good analytical skills and finite volume numerical methods (desirable)
• Proficient in analysing large model datasets preferably with python.
• Experience with coupled models such as waves, suspended sediments, or biogeochemistry would be desirable.
• Good track record of translating research into impactful publications, presentations, reports and code repositories
• Proven ability to manage one’s own workload and collaborate with colleagues
• Successful experience in contributing to funding procurement is desirable
• Interest in new frontiers of data-model integration (e.g. machine learning, digital twins) is welcome.

PML is a highly impactful organisation, exemplified by our impact case studies which scored very highly with 100% deemed to be world-leading or internationally excellent by the 2020 NERC evaluation.  We strive to deliver excellent research that can benefit the environment and society and have clear strategies in place to support our staff to achieve academic and non-academic impact.   Applicants to PML should have at least a basic understanding of the UK impact agenda.   PML offer training in impact and provide tools and guides, through our dedicated Impact Team, to help further understanding and skills in these and associated areas.  In addition, our Science to Impact Challenge Areas coordinate activities to work inter-disciplinarily towards shared goals to help alleviate or mitigate global challenges, such as climate change and biodiversity loss.  PML encourages applicants that aspire to work collaboratively and creatively to make a difference.

PML is committed to equality, diversity and inclusion, and our policy can be found here: https://www.pml.ac.uk/Working-with-us. We are proud to have achieved the Athena SWAN award as recognition of our achievements in gender equality. As part of this, we offer opportunities to discuss flexible working and whilst the selection process will be based on merit, we particularly welcome applications from female candidates, currently underrepresented.

 *PML offers annual salary increments over a five year period, rising to £39486 (Scientist Grade)