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Job description We are looking for two highly creative and motivated PhD students to perform research in the context of the Advanced ERC Grant ACME ("Assumption-lean (Causal) Modeling and Estimation
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a step-change in our ability to observe, quantify and understand forest disturbances and recovery by using time series of the most detailed structural and radiometric 3D forest models ever built
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privacy-preserved fashion. Research topics include, but not limited to, i) handling distributed DL models with data heterogeneity including non i.i.d, and domain shifts, ii) developing explainability and
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wireless technologies. You implement the designed solutions on embedded hardware platforms and experimentally validate their performance. Experimental validation can be backed by modelling or theoretical
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. Defining predictive tasks based on clinical goals. Selecting and setting up appropriate data preprocessing pipelines. Training and evaluation of computer vision models. Internal and external algorithmic