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, Physics, Computer Science, or a closely related discipline. The ideal candidate will have: A strong background in radar, microwave engineering, signal processing, electromagnetics, machine learning
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Applicants should hold a degree-level qualification in a relevant discipline such as: Electrical or Electronic Engineering; RF or Microwave Engineering; Applied Physics; Microsystems or Microengineering
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profile for PhD 1: An MSc degree in electrical engineering or a closely related field, with strong experimental academic results. A solid foundation in analogue electronics, RF or microwave engineering
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. Python, MATLAB, or similar); excellent written and spoken English. Prior experience with superconducting circuits, low-temperature physics, optics, microwave engineering, or nanofabrication is welcome but
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and its supporting infrastructure • realize on-chip pulsed DNP • design microwave pulse sequences for on-chip DNP using spin physics, numerical simulation tools, and quantum optimal control
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academic record, interested in doing scientific research towards a PhD degree. A solid background in RF/microwave engineering is required, including familiarity with concepts such as S-parameters, nonlinear
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desirable: microwave engineering, confocal microscopy, scanning probe microscopy, magnetic resonance spectroscopy, and scientific programming in Python. Prior experience with hardware electronics such as
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technologies. The institute places particular emphasis on micro- and nanotechnologies, including nanostructures and nanoelectronics, microelectronics, microwave engineering, and microsystems. PhLAM is a Joint
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-resolved simulations. In case a fluidized bed is chosen, a traditional Eulerian Two-Fluid model (TFM) will be compared with a novel Lagrangian Continuous Particle Model (CPM). Initially, engineering
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geometries and combine common materials in new ways to build bespoke, miniaturised antennas using magnetic nanoparticle structures. Your designs will make it possible to integrate digital technology platforms