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Field
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required to take part in at least three lab courses. These method-based courses last for up to five days and constitute an important element of the study programme, with students receiving intensive training
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the development of sensitive quantitative assays for in vitro and in vivo approaches; improved measurement techniques that ideally push resolution limits to the single molecule level; statistical methods to deal
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symposium Advanced methods and specialised training Transferable skills and career development Other curricular activities including an IMPRS-ML retreat In addition to the curricular activities organised by
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methods courses and courses on advanced neuroscience and transferable skills, make excursions to research institutions and companies and participate in summer schools, seminars and international meetings
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reinforcement tasks to work with, enhance or replace established methods from computational engineering and computer simulation (such as the finite element method) to represent and exploit relationships along
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) scientific studies Experience with relevant field data collection methods (e.g. chamber- or eddy covariance-based C flux measurements, biodiversity sampling methods) Computer programming skills (e.g. Matlab, R
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signal processing methods and a modelling environment, aided by unique hardware-in-the loop, to assess the detection and estimation algorithm performance and determine optimal multistatic configurations
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have the opportunity to exploit some of the cutting-edge experimental and computational methods, comprising constraint-based and kinetic modeling, statistical analysis of large datasets, high-throughput
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implementation of these within optimized computer code, but also large-scale applications of the resulting methods to various chemical problems of interest. Candidates with a strong background in theoretical and
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the KNAW Early Career Award, I can further integrate innovative methods and automation into fungal research, advancing how we visualize, quantify, and interpret the hidden dynamics of mycorrhizal fungi