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: Machine Learning/Pattern Recognition 2. Objectives: Lifelong Incremental Learning for Navigation in Dynamic Industrial Environments 3. Requirements for admission and hiring: - Hold a BSc degree in
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following mandatory requirements: a) A completed degree in Computer Engineering; b) Good knowledge in the areas of Machine Learning, Natural Language Models, and Computer Security – information to be provided
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for the analysis of complex experimental data; • Development and implementation of strategies for multiomics data integration and systems biology; • Use of Python and R for statistical analysis, machine learning
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the deadline for applications is required, in the contracting phase, including those resulting from academic degree recognition processes. Preferred factors: Knowledge of Machine and Deep Learning; Knowledge in
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from academic degree recognition processes. Preferred factors: Knowledge of Machine and Deep Learning; Knowledge in data exploration and processing; Knowledge of Generative AI models n mainly LLM's
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statistics and/or machine learning, particularly in multivariate analysis (e.g., principal component analysis, regression) and data integration methods; Experience in scientific research activities
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Operations & Technology Knowledge Center, with the following conditions: MAIN FIELD:………..…………………………………………………………………………………………… Management, with particular focus on the intersection of: Machine Learning Causal
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 28 days ago
data sharing (preferred); good knowledge of machine learning algorithms; proficiency in high-level programming languages (e.g., C++, Python, C#, etc.) (preferred); knowledge of database formulation and
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 28 days ago
field. This project involves: general literature review on information retrieval strategies using emergent tools, such as machine learning, semantic embeddings, etc… for the particular case of waste-to
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:………..………………………………………………………………………………………………………………………………………… Management, with particular focus on the intersection of: Machine Learning Causal Inference Applied Field Experimentation Scientific Areas: Management, Economics, Information Systems, Computer Science, Data