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Field
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://elliit.se ) and focuses on enabling reliable robot situational awareness in challenging and unpredictable environments. The project is grounded in statistical, model‑based methods that combine multi‑object
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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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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | about 1 month ago
science as part of the ERC Starting Grant project Incorwave, which aims to develop advanced numerical and mathematical methods for passive seismic imaging. The research will focus on two key-directions: (1
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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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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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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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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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) 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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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
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applications for a PhD candidate focusing on the use of natural language processing (NLP) methods to advance climate impact research. The overarching goal is to develop a benchmark dataset on the socioeconomic