Post-doctoral researcher modeling transport in the tokamak pedestal

Post-doctoral researcher modeling transport in the tokamak pedestal

Published Deadline Location
4 Mar 6 May Eindhoven

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Would you like to work in a scientific environment as a post-doctoral researcher? We are looking for a postdoc with good understanding of plasma transport physics and experience with (integrated) transport solvers.

Job description

Post-doctoral researcher modeling transport in the tokamak pedestal (X/F/M)

DIFFER is seeking to hire a post-doctoral researcher for approximately two years to work with the Integrated Modeling and Plasma Micro-Turbulence groups at the institute within multiple EUROfusion frameworks to conduct simulations and design and improve transport models applicable to the pedestal and connecting to the far plasma edge.

Additional collaborative projects with the NLeScience centre are also foreseen.

Understanding of anomalous transport in fusion experiments resulting from micro-scale instabilities and turbulence, has increased substantially in recent years, and substantial progress is now visible regarding turbulence in the H-mode pedestal in tokamaks. However, to date models for the transport across the pedestal are scarce and do not account for all relevant physics required for a reactor-scale tokamak in this region of the plasma (high-power, high-density, power-losses from radiation etc). Furthermore, L-mode edge transport modeling also requires further improvements, particularly with respect to the L-to-H transition.

Specifications

DIFFER

Requirements

Responsibilities and tasks:
  • Re-derive and upgrade existing transport models
  • Implement models in existing transport solvers
  • Benchmark models against other simulation frameworks
  • Deploy the resultant improved solver to model specific discharges and interpret the physics at play
  • Uncertainty Quantification of model parameters in transport codes
  • Employment reactor scale simulation, allowing launching tools that allow UQ to be automated.

Required skills:
  • Good understanding of plasmas transport physics
  • Experience with (integrated) transport solvers, e.g. JINTRAC
  • Knowledge of turbulence physics
  • (optional) Experience with uncertainty quantification tools such as dUQtools or similar for improved validation of simulations against experiments
  • (optional) Knowledge of edge/SOL and pedestal turbulence & MHD stability physics
  • (optional) Experience with gyrokinetic simulations

Conditions of employment

This position is for 0,8 FTE, will be for a period of 2 years and is graded in pay scale 10. The position will be based at DIFFER (www.differ.nl) and the working location will be at TU Eindhoven. When fulfilling a position at DIFFER, you will have an employee status at NWO. You can participate in all the employee benefits NWO offers. We have a number of regulations that support employees in finding a good work-life balance. At DIFFER we believe that a workforce diverse in gender, age and cultural background is key to performing excellent research. We therefore strongly encourage everyone to apply. More information on working at NWO can be found at the NWO website (https://www.nwo-i.nl/en/working-at-nwo-i/jobsatnwoi/)

Employer

Dutch Institute for Fundamental Energy Research

The Dutch Institute for Fundamental Energy Research (DIFFER) performs leading fundamental research on materials, processes, and systems for a global sustainable energy infrastructure. We work in close partnership with (inter)national academia and industry. Our user facilities are open to industry and university researchers. As an institute of the Dutch Research Council (NWO) DIFFER plays a key role in fundamental research for the energy transition.

We use a multidisciplinary approach applicable on two key areas, solar fuels for the conversion and storage of renewable energy and nuclear fusion – as a clean source of energy.

Specifications

  • Postdoc
  • Natural sciences
  • max. 32 hours per week
  • Doctorate
  • 3372

Location

De Zaale 20, 5612AJ, Eindhoven

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