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Field
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. Strong knowledge of signal processing. Extensive experience designing, training, evaluating, and publishing deep neural network models. Strong scientific writing skills. Strong programming skills in python
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healthcare challenges, particularly in varies areas related to allied health, nursing and community health. Conceptualize, design and implement innovative projects based on deep understanding of healthcare
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intelligence. Strong knowledge and research outputs in AI, particularly in the field of deep learning, knowledge representation and reasoning, or neuro-symbolic AI. Proven commitment to proactively keeping up
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computer vision and vision-language models Experience with ML evaluation metrics and benchmarking Proficiency in Python and deep learning frameworks (e.g., PyTorch) Interest in applied, industry
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with remote sensing data (satellite, aerial, hyperspectral, SAR, LiDAR) Computer Vision Natural Language Processing Remote Sensing Machine Learening and Deep Learning Reinforcement Learning Large
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of deep learning, specifically, foundation models, diffusion models is a must. 1) For image/video watermarking: In depth knowledge of AI editing methods and property of generative models. 2)For video
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· Lead the design and implementation of mixture-of-experts neural architectures and reinforcement learning pipelines for counterfactual disease trajectory simulation for EMED, an NIH-funded multi-modal AI
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interpersonal and communication skills and the ability to present technical information effectively to a range of audiences. Knowledge of quantum and nonlinear optics is desirable, as well as knowledge of deep
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of Applied Learning, the Singapore Institute of Technology (SIT) works closely with industry partners to deliver translational, impact-driven research. This role supports applied food processing
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experimental research involving imaging systems, instrumentation, data acquisition, and quantitative validation is highly desirable. Familiarity with AI/deep learning methods for medical imaging is advantageous