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in topological materials and eagerness to work on tough experimental challenges. We expect the candidates to have: PhD degree in physics or in a nearby field Experience on 2D materials and quantum
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will design and implement novel computer vision and machine learning methods for “sensorized” cameras that extract medically relevant features without transmitting raw video. You will evaluate algorithms
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Agents and remote interfaces to support the MaaS Consumer to remotely monitor and control parameters provided by the MaaS Provider. Requirements The candidate must possess doctoral degree (PhD) in any
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identification algorithms that directly interface with physical hardware. We work closely with industry partners, and our research has led to several methods now used in commercial products. We are part of
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traits – and link these traits to epigenomic variation profiled via whole genome bisulfite sequencing. The candidate will also have the opportunity to explore advanced pangenome-based methods to probe
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). Contribute actively to the project and the host institution’s research community. Eligibility and assessment Applicants must hold a PhD (candidates who are in the final stages of completing their doctoral
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, cleanroom fabrication, performing cryogenic microwave measurements, and data analysis. You are expected to participate in advising and mentoring PhD students. Your experience and ambitions
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your application and look forward to welcome you to our open stimulating research environment. Requirements Candidates must hold an internationally recognized PhD degree in quantum physics research
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must hold a PhD (candidates who are in the final stages of completing their doctoral dissertation may also be considered), demonstrate the ability to conduct independent research, and have prior
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a doctoral degree in demography, public health/epidemiology, statistical sociology, statistics, population genetics or other relevant field, have strong quantitative methods skills and an excellent