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time at NY Creates Albany NanoTech Complex, where you will collaborate with staff using 193 nm deep-UV ltihography to fabricate devices at 300mm-wafer scale. Essential Duties and Responsibilities: You
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: Verifiable world models. The research will focus on developing a new class of structured, verifiable world models that integrate the flexibility of deep learning with the rigor of formal methods and
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. Familiarity with machine learning (ML) techniques for optimizing models or analyzing complex datasets. Experience with space-based instrumentation or similar high-precision systems. Demonstrated expertise in
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will work with tools such as AlphaFold and RosettaFold-diffusion and apply deep learning to address the next challenges in dynamics and the design of novel protein-based therapeutics. As postdoc, you
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multimodal deep learning models that integrate imaging and clinical data to personalize treatment and follow-up strategies. In the Netherlands, around 75% of patients with an abdominal aortic aneurysm (AAA
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Education and Experience: Appropriate PhD in a related field. Preferred Qualifications: Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in
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intelligence or related areas such as deep learning and decision support systems. Candidates with a background in other areas such as the application of data analytics in healthcare and biomedical applications
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 19 days ago
to motion and respiration. Over the past years, we led several works in this area. Particularly, we developed several deep learning models for the segmentation of SC lesions either from T2 sagittal MRI
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areas such as deep learning and decision support systems. Candidates with a background in other areas such as the application of data analytics in healthcare and biomedical applications will also be
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management Cognitive radio or adaptive communication systems, including dynamic spectrum access, band selection Heterogeneous network architectures, including terrestrial and non-terrestrial networks Deep