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(university diploma or master's degree) in the field of geosciences, engineering or physics. Ideally, you have knowledge of numerical methods and experience with common programming languages (e.g. Matlab
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Cendón CALL DETAILS Tasks to be carried out: Collaborate in research tasks related to new mathematical models and numerical methods for the valuation of renewable energy certificates (RECs) and their
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datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning). The goals are to develop new computational methods that allow the scientific inference
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in vacuum using a laser focused through a high numerical aperture objective. The laser produces an optical force equivalent to a mechanical spring, and the system can be regarded as a mass-spring
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such as multiple fragmentation methods, high-resolution Fourier Transform Ion Cyclotron Resonance mass spectrometry, two-dimensional mass spectrometry, trapped ion mobility spectrometry, and chemical
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innovative building technologies. You are passionate about exploring novel built environment control methods, with a particular focus on how to integrate smart materials into energy-efficient indoor air
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health behaviors. The position may include some classroom teaching in statistics and/or research methods. The position affords opportunities for professional development and advancement, with guidance
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alarm signal or take other actions locally. We aim to implement methods for quality control and enhancement of data quality through approaches developed in other PhD projects within SFI Smart Ocean. These
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to describe a condition or make a decision to send an alarm signal or take other actions locally. We aim to implement methods for quality control and enhancement of data quality through approaches developed in
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. To do this, knowledge or willingness to be trained in advanced statistical modelling, ideally with an interest in methods for causal inference in observational data, is strongly preferred. Using various