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Online applications must be received before 11:59pm on: July 6, 2025 If a date is not listed above, review the Applicant Instructions below for more details. Available Title(s): 306-YN_FACULTY
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., Nature Cell Biology, 2018). The Teixeira lab investigates the roles of spatial organization in biological processes and develops DNA nanotechnology-based tools to map and manipulate membrane protein
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that also act as green energy producers driving the societal transition towards net zero. In this position, you will build on your expertise in IoT and low-power computer and communication systems to research
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experience in physiological signal processing (e.g., EMG, EEG, ECG) is an advantage. Familiarity with HCI principles and frameworks, in particular, experience conducting usability studies and designing user
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at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6. Interviews
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on computer networking and distributed systems, computer security and privacy, and software engineering. Both research and education are conducted in close cooperation with international, national, and regional
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, statistical signal processing, optimization theory, machine learning and artificial intelligence. The candidate is expected to actively participate in experimental work focused on building datasets of channel
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
. The candidate must have hands-on instrumentation experience and ability to connect this to atmospheric radiative transfer through an understanding of data processing and analysis. A successful candidate will have
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document will provide information of what criteria will be assessed at each stage of the recruitment process. HR Use Only (Research G6 Clause): * Please note that this is a PhD level role but candidates who
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of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, general pre-trained transformers, prompt engineering, knowledge graphs, knowledge