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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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developing statistical and machine learning approaches for the analysis of CRISPR base editing screens and their integration with large-scale genomic annotations derived from variant effect predictors
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. They should be able to thrive in the multidisciplinary culture of INESC MN and fit in projects involving physics, microfabrication, machine learning, mechatronics, etc. and be able to communicate
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mixed reality (MR) strategies to blend information derived from machine learning and computer vision processes to the workers' expertise. The objective of this project is to develop and evaluate MR
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AI and Federated Learning concepts;; - Demonstrated leadership capabilities. Research FieldEngineering » Computer engineeringYears of Research ExperienceNone Research FieldComputer science
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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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: Machine Learning/Pattern Recognition 2. Objectives: Mitigating Negative Transfer in Incremental Task Learning for Industrial Ground-Based Drones. 3. Requirements for admission and hiring: - Hold a BSc
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-award courses of Higher Education Institutions. Preference factors: Machine Learning Knowledge. Knowledge of signal processing and machine learning libraries (e.g., PyCaret, scikit-learn). Minimum
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of these areas:a. Data Science (Python)b. Machine Learning (Python)c. Remote Sensingd. Internet of Things (Hardware, Node-red, JavaScript)e. Satellite Image Processingf. R&D and scientific
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optional skills and qualifications: Previous research experience, particularly in the fields of Internet of Things security and machine learning model security applied to intrusion detection. Contracting