Scientist within data-driven and numerical ocean modeling

About this job

About the roles Modern meteorology and oceanography requires management and analysis of enormous amounts of data, and offers great and exciting professional challenges. Since the institute was established in 1866, Norwegian meteorologists and scientists have played a key role in this development. The Norwegian Meteorological Institute (MET Norway) is today an internationally leading operational forecast and research institution with expertise in operational meteorology, oceanography and climate science. The primary area of interest coincides with the national focus area, northern Europe, North Atlantic and the Arctic. The division for Ocean and Ice conducts world class research and operates 24/7 forecasting of storm surge, ocean currents, hydrography, and sea-ice on regional to coastal scales. As well as multi-decadal hindcasts and reanalyses. These models provide input to downstream services such as oil spill drift models and search-and-rescue support. The work is carried out in collaboration with national and international partners. MET Norway utilizes the Regional Ocean Modeling System (ROMS) as the dynamic core for our operational forecasting systems, primarily the Norkyst and Barents models. These high-resolution tools provide essential data on ocean currents, storm surges, and sea-ice, supporting diverse marine operations, research, and downstream services like oil spill drift modeling and search-and-rescue. We continuously advance these capabilities through close collaboration with the Institute of Marine Research (IMR) and international partners, with current efforts focused on consolidating our common model code base and developing new high-resolution domains for the Barents Sea and Svalbard. Data-driven methods have a great potential for making our ocean and sea-ice forecasting systems more computationally efficient, and also make them more accessible for cross-disciplinary work relevant to marine ecosystems and the blue economy. We also acknowledge that other institutions, both in Norway and abroad, are investing substantial resources in the development of data-driven methods relevant to our core mandate, and it is therefore essential to establish and maintain strong links with other groups in the field. We are therefore announcing a permanent position for a scientist focusing on both data-driven ocean modeling, science dissemination, and external collaboration on methods developments. The successful candidates will be employed at the Division of Ocean and Ice in Oslo and collaborate with experienced scientists at MET Norway as well as partner institutions in Norway and abroad. Position 1: Data-Driven Ocean Modeling The successful candidate will work in externally financed projects to develop data-driven ocean models for prediction and coastal downscaling. Using Graph Neural Networks and similar machine learning techniques trained on archives of dynamic ocean models, the candidate will create hyper-resolution models relevant to cross-disciplinary research, such as marine ecosystems, and decision-making tools for the blue economy and coastal governance. Position 2: Numerical Ocean Modeling The successful candidate will join the Ocean and Ice division to play a pivotal role in the development of our next-generation models based on the Regional Ocean Modeling System. Responsibilities include the full lifecycle of model development: from defining domains and creating necessary input data, to rigorous testing, operationalization, evaluation, and dissemination of results. Qualifications and Expected Experience PhD in oceanography, meteorology, physics, cybernetics or applied mathematics is required Sound understanding of physical oceanography and experience in numerical modeling Knowledge of general machine learning methods, and in particular application of data-driven prediction for geophysical applications Knowledge of contemporary ocean modeling and data assimilation techniques is required The candidate should bring an established network in relevant science fields Proven experience with science dissemination and outreach is required Success with peer-review publishing of results is required Particular emphasis will be given on the candidates ability to work as part of a team Expected Technical skills Experience in software development and scientific data analysis in Python is required and knowledge of Fortran is beneficial Experience and proven knowledge in applied mathematics/scientific programming in the Linux environment is required Experience with python-based tools for data-driven prediction (e.g. Pytorch, Anemoi, etc) is required for position #1, and beneficial for position #2 Knowledge in handling geophysical data formats and libraries (e.g. Netcdf, CF-conventions, zarr, xarray) Experience with high performance computing is required for both positions. Additionally, experience with the application of GPU infrastructure is required for position #1 Experience with software version control (e.g

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