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selection criteria Peer-reviewed publications in relevant fields. Experience with modelling and simulation, e.g. machine learning, parametric design, or finite element tools (Abaqus, Ansys, etc.). Relevant
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with large-scale data analysis, such as genomics or transcriptomics data Experience with a workflow management system such as Snakemake or Nextflow A willingness to learn and apply machine learning
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of this annex, as well as to: Programming in Python and R. Statistical classification and machine learning methods: SVM, neural networks and logistic regression. 3.2. Qualification: Official Master’s degree in
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of the) [map ] Subject Area: Mathematical Machine Learning Appl Deadline: 2025/10/13 11:59PM (posted 2025/09/16, listed until 2025/10/13) Position Description: Apply Position Description Join Us! Are you
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spanning design, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication
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driving, in-car monitoring, industrial automation, and security surveillance. The research, called "R4DAR," aims to leverage emerging 4D imaging technology with Massive MIMO to create image-like radar
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crucial; Design interventions to reduce bias and improve fairness and safety in human-AI interaction. The research will combine computational modeling (e.g., NLP, machine learning, deep learning) with human
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 3 days ago
with Machine learning approaches, to refine the ataxin-3 network. The most affected PPIs, will be validated using commercial fibroblasts from MJD patients, and standard molecular tools such as Western blotting
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emotion safety is crucial; Design interventions to reduce bias and improve fairness and safety in human-AI interaction. The research will combine computational modeling (e.g., NLP, machine learning, deep
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6. of this Notice. Preferred factors: Knowledge in machine learning and programming (Python), deep learning (e.g., tensorflow, pytorch) and time-series modeling in marine ecology applications