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in the Phi_Lab, led by Dr. Azeem Ahmad, and will focus on the development of advanced reconstruction algorithms and next-generation quantitative optical microscopy and tomography systems for imaging
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corresponding to different subsets of sensors. Such an approach is NP-hard. Given an upper bound on the number of attacked sensors, and so-called sparse observability condition algorithms have been proposed using
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reproducible research practices. Your responsibilities Develop and implement computer vision and image processing algorithms for star tracking and satellite detec-tion using event cameras. Design and build a
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of Physics and Technology . The position will be hosted in the Phi_Lab, led by Dr. Azeem Ahmad, and will focus on the development of advanced reconstruction algorithms and next-generation quantitative optical
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applications for a Post-Doctoral Associate position, in the area of Quantum Algorithms. The candidate is expected to conduct research in computer science focusing on the combinatorial aspects of quantum
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training datasets; Design and carry out laboratory experiments to produce representative experimental training data; Develop physics-informed machine learning algorithms, trained on both numerical
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chromatography/mass spectrometry (LC-MS) measurements using principal component analysis, partial least squares, genetic algorithms, and other multivariate statistics. Current projects have accumulated a
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candidates will be required to fund the difference between the home fees and international fees. Overview Are you interested in developing Brain-Computer Interface technologies to control brain stimulation in
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, plant and planetary health. The microbial diversity in different niches is enormous, and it is not all bacteria or viruses that are harmful and many are even beneficial. We are constantly faced with
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formula is true or false (EXPTIME vs NP). Can we develop and implement efficient algorithms for this problem? This problem has been attacked using multiple different methods for the past 40 years, without