294 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Ulster University" Fellowship research jobs in Singapore
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dynamics (MD), or ab initio molecular dynamics (AIMD), to investigate polyamide interfacial polymerization, interfacial reactions, or transport mechanisms. • Experience in data-driven modeling or machine
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of marine geophysical survey and machine learning algorithms; Job Requirements: A Bachelor degree in geophysics or equivalent and A PhD degree in geophysics / geomechanics or equivalent from a recognized
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machine learning models and neural circuits in the brain process states of emotion. The Nair group combines cutting-edge systems neuroscience tools with the development of new AI methods to understand and
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aquaculture (e.g., behavioral analysis, growth prediction, digital twin, computer vision.) Develop, train, and validate advanced computational models and machine learning algorithms tailored to complex datasets
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. • Familiarity with reinforcement learning and more generally machine learning. • Experience with communication protocols such as LoRaWAN, Zigbee, BACnet, Modbus, and IoT integration using MQTT and RESTful APIs
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow. We welcome you to join our community
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equivalent. Strong background in machine learning and computer vision. Prior experience in data-efficient classification, synthesis, and detection is preferable. Strong publication records in top-tier machine
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is to develop real-time truck-drone collaboration system to enhance Singapore safety and resilience and using learning-based approaches. Key responsibilities include: Collecting and analyzing relevant
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an active role in data management, processing, and quantitative analysis (e.g., longitudinal and multilevel modelling, time-series or high-frequency data analysis, machine learning or predictive
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-machine teaming. Moreover, the consequences of such digital transformation are explored in the context of workforce and labor developments, organisational innovation, and learning/education. About the