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ASIC implementation. You will carry out system modelling, design novel parallel processor architectures at the RTL level (using Verilog/SystemVerilog or VHDL), and drive the hardware-software co-design
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 21 days ago
. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). The Goddard Earth Observing System (GEOS), developed by NASA’s Global Modeling and Assimilation Office
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Are you interested in advanced rheological characterization, microstructure analysis, and modelling of complex food systems? In this postdoctoral project, you will combine fundamental science with
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and (scientific) writing skills. Due to the international character of our research, good command of spoken and written English is essential. We highly encourage applicants from all members of our
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the development of therapeutic strategies to promote neurological recovery. The successful candidate will use a combination of in vivo and in vitro approaches, including animal models, molecular and
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language models, multi-agent systems, reinforcement learning and knowledge evolution, evaluated using industry operational datasets. These positions offer an opportunity to advance autonomous decision-making
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, ECG, GSR and other biosignals. Multimodal data analysis Machine learning and advanced statistical modeling Research experience in perception, consciousness, cognition, or emotions will also be valued
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-registered multiplex immunofluorescence (mIF) and H&E whole-slide images, all linked to comprehensive clinical annotations. This is complemented with mechanistic mouse models to functionally establish immune
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learning models (e.g., multimodal AI, large language/world models) with specific finetuning for ELEVATE; designing geographically context-sensitive urban design recommendations that promote active mobility
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intelligence and large language models for data analysis, and bioscientific programming. The candidate should have experience in the analysis of large-scale biomedical data, e.g.: omics or clinical data, using