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: Experience in Computer Vision and machine learning. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding valuation: the first phase comprises the Academic Evaluation (AC
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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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Requirements Academic qualifications: -. Minimum profile: Experience in Computer Vision and machine learning. Preference factors: Experience in research projects, and writing of scientific papers. Research
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, and writing of scientific papers. Minimum requirements: Experience in Computer Vision and machine learning. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding
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, and writing of scientific papers. Minimum requirements: Experience in Computer Vision and machine learning. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding
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-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: 1. Formulate and validate automated inspection methodologies based on computer vision and AI techniques
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: Experience in Computer Vision and machine learning. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding valuation: the first phase comprises the Academic Evaluation (AC
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of programming and artificial intelligence.; - Knowledge of deep learning and computer vision.; - Autonomy. Minimum requirements: Strong knowledge of the English language (written and spoken). 5. EVALUATION