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active research interests in quantum computing, quantum algorithm/software development and applications in decarbonisation who can take full advantage of the unique opportunities the QDA provides
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computational models, algorithms, or theory to probe the mechanisms of learning and memory. Ideal candidates will work across levels—from molecules and synapses to circuits and systems—and contribute
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Master Thesis - Development of ligand conjugated lipid nanoparticles for targeted T cell delivery...
holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms (AI) to analyze large imaging and molecular
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of 22q11.2 and 3q29 deletion syndromes, two rare conditions that confer the highest genetic risks of schizophrenia. Key Responsibilities: Develop and implement advanced algorithms for analyzing calcium
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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
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in developing new tools to understand the nervous system and to explore theories behind neural phenomena. As for developing new tools, we have been working on network alignment algorithms [FCC+21] and
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Algorithm-HW-Codesign for wireless signal processing investigate novel hybrid imaging and coded excitation approaches for medical ultrasound reliable and resilient communications for critical applications in
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train robust machine learning (ML) algorithms without exchanging the actual data. The benefits of such a decentralized technology over personal and confidential data are multiple and already include some
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revisit discretization methodologies in view of modern requirements and computational capabilities. The candidate will focus on developing mesh generation algorithms meeting the following criteria
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. The monitoring of telecommunications and energy production and distribution networks are characteristic examples of such time-critical applications. The project aims to propose unsupervised online CPD algorithms