PhD in Polar Ocean Modeling & ML Surrogates

Danmarks Tekniske Universitet; Denmark; On-site; DKK 420,000 - 620,000; Full time

Job summary

DTU Space in Denmark seeks a PhD candidate to work on assimilating SWOT observations into a high-resolution ocean model focused on Polar Regions. The project emphasizes developing surrogate models with Scientific Machine learning to reduce the computational cost and enable efficient exploration of ocean processes.

The candidate should have a background in ocean modelling and remote sensing, preferably with satellite altimetry experience and MITgcm, and be prepared for international collaboration

Qualifications

• Background in ocean modelling and remote sensing.
• Experience with satellite altimetry and ocean modelling frameworks.
• Wamiliarity with high-resolution ocean models is desirable.

Responsibilities

• Assimilate SWOT observations into a high-resolution ocean model.
• Develop surrogate models using Scientific Machine learning to reduce computational cost.
• Collaborate with SWOT researchers and international partners.

Skills

Ocean modelling

Remote sensing

Satellite altimetry

High-performance computing

Education

Two-year Master’s degree (120 ECTS)

Tools

MITgcm

Scientific machine learning

Job description

DTU Space in Denmark seeks a PhD candidate to work on assimilating SWOT observations into a high-resolution ocean model focused on Polar Regions. The project emphasizes developing surrogate models with Scientific Machine learning to reduce the computational cost and enable efficient exploration of ocean processes.

The candidate should have a background in ocean modelling and remote sensing, preferably with satellite altimetry experience and MITgcm, and be prepared for international collaboration