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Field
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: Translate ML-based error-correction / DPD algorithms into hardware-friendly forms (model reduction, sparsity, quantization, fixed-point design). Design the architecture and RTL of a low-power accelerator that
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technologies such as IoT, big data, analytics, computer vision, cloud computing, and artificial intelligence (AI). IoT devices help in data collection. Sensors plugged in tractors and trucks as well as in fields
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Allowance** EUR 4736 EUR 710 EUR 660 Context: Agriculture and agronomy generate a wide variety of data (connected equipment, weather, environmental sensors
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fidelity, enabling precise characterization of transmitter errors and nonlinearities. These measurements will be used to generate error signals for advanced AI-assisted digital predistortion algorithms
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presents significant challenges. These include enormous data bandwidths, sophisticated optical control, advanced rendering pipelines, and new algorithms that can tightly integrate physical hardware, sensors
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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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sequences. Development the analysis method and algorithm. 12 to 24 months: Photothermal, photoacoustic and hotspot characterization of several nanoagents with a significantly different hotspot effect
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21.12.2021, Academic staff The Department of Computer Science, Technical University of Munich, has a vacancy for a PhD candidate/researcher position in the area of efficient algorithms. The position
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to be essential. Certain conflicting objectives then arise (computation time, optimality of the solution, design and implementation time of the algorithm used, etc.). For the engineering researcher, who
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twins, enabling real-time stress-testing under simulated edge cases like cyber-physical attacks and sensor failures. The Research Challenges There exists a complex interplay of factors that present