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pressure and temperature levels; - Validate the numerical model of the complete system by comparison with experimental data; - Identify improvement strategies for performance and system robustness. Work
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Physics Group at Princeton University.The successful candidate(s) can play a major role in one or more of the following: 1) analysis and publication of Energetic Neutral Atom (ENA) and other observations
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well as computational analysis to uncover biophysical principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine
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. A background in forest engineering, ecohydrology, and/or ecology would be ideal but is not required. Experience in numerical modelling, big data analysis, and plant ecological and physiological
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the areas of fluid dynamics, turbulence and net-zero combustion. There is substantial scope for the student to direct the project with the main focus on (i) Generating an advanced Direct Numerical Simulation
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processing, time series analysis or machine learning for the interpretation of structural data is desirable. Basic knowledge of numerical analysis and design of structures for special load cases (earthquakes
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-assisted simulation framework by providing accurate high-fidelity numerical data for training and validation of surrogate models for multi-disciplinary design and optimization. · Participating in
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analysis Physics » Applied physics Physics » Computational physics Researcher Profile First Stage Researcher (R1) Country Switzerland Application Deadline 23 Nov 2025 - 22:59 (UTC) Type of Contract Temporary
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• Strong quantitative and programming skills; experience with seismic data analysis or numerical modelling is highly desirable• Excellent written and verbal communication skills• Ability to work
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(sequence homology- or protein structure-based) Familiarity with UNIX/LINUX-based operating systems and shared compute infrastructure Proficiency in Python, R, or similar languages for data analysis