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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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of seismic methods and numerical simulations, Good PC and programming skills (e.g., with Python, MATLAB), Experience with measurement techniques and field measurements using sensor technology (ideally using
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13.01.2020, Wissenschaftliches Personal PhD position at the Chair of Algorithms and Complexity. Candidate shall work on approximation algorithms for scheduling problems in parallel and distributed
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%). The position will be offered for three years and will have as topic the classical emulation of quantum algorithms for the simulation of complex quantum systems. The position will be based at the Institute
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architectures, and demonstration of showcase applications, like light emitters, light sensors, supercapacitors, and batteries. Research and training tasks will be carried out by a collaborative and
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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research on biomedical sensor applications (biomedical sensor interfaces/ integrated mechanical strain sensors) analog/Mixed-Signal Integrated Circuit Design (CMOS, low-power, low-noise design) publication
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, on fundamental aspects of atomic spectroscopy and quantum physics, and will finally learn how to develop a commercial quantum sensor. Your role: Basic research in the theory and experiments with hot