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summary: "We are recruiting full-time Research Fellows to develop hybrid physics-AI for weather applications."
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summary: "We are recruiting full-time Research Fellows to develop hybrid physics-AI for fluid mechanics and fluid-structure interaction, towards weather applications and engineering applications in the maritime sector."
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details:
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- content:
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- "**Location:** Singapore"
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- "**Type:** Full-time"
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- "**Deadline:** Open until filled"
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- heading: "The Team"
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content: "MathEXLab is an intesrdisciplinary research lab at the National University of Singapore (NUS), led by Assistant Professor Gianmarco Mengaldo. We develop next-generation mathematical modelling and AI methods for understanding and predicting complex systems, with applications in weather and climate, fluid mechanics, robotics, and socio-technical systems."
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content: "MathEXLab is an intesrdisciplinary research lab at the National University of Singapore (NUS), led by Assistant Professor Gianmarco Mengaldo. We develop next-generation mathematical modelling and AI methods for understanding and predicting complex systems, with applications in weather and climate, fluid mechanics, robotics, and socio-technical systems. NUS AI Institute was established on 25 March 2024 at the National University of Singapore, under the direction of Professor Mohan Kankanhalli, Provost’s Chair Professor of Computer Science. The institute aims to bring together AI researchers across NUS, spanning foundational and applied AI and its societal impacts — combining core research with deep domain expertise to harness AI for the public good."
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- heading: "What you will do"
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content:
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- "Experience with real-world geospatial/sensor data, including quality control, cleaning, and visualization."
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- "Strong communication and collaboration skills."
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- "Deep learning expertise in generative models, physics-aware learning, or uncertainty modelling is highly desirable."
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- "Experience with dense spatiotemporal prediction, such as video prediction or precipitation nowcasting, is highly desirable."
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- "Atmospheric science or tropical meteorology background is a plus, but not required."
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- "Experience with dense spatiotemporal prediction, for example computational fluid dynamics applied to weather and climate, is highly desirable."
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