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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 2 months ago
Sciences, Biochemistry, Biomedical Engineering, Biotechnology, or related fields, with proven experience in electrochemical sensors development and application and immediate availability to start the
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membranes for efficient plasma delivery to electrochemical sensors. Characterize plasma separation performance including separation time, yield, cell carryover, and robustness across physiological and
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-enabled interactive platforms, embedded multimodal interfaces • Design and integrate hardware components such as sensors, actuators, and microcontrollers. • Build and iterate prototypes using rapid
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(TASC) program of the ARC Industrial Transformation Research Hub for Intelligent Contaminant-Sensing in Complex Environments (IC-SensE). The TASCprogram explores consumer and workforce adoption of sensor
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systems (e.g., Arduino, ESP32, or similar platforms) Experience developing or adapting custom instrumentation and sensor systems for field research applications. Experience integrating physiological
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. The analyses will include large-scale epidemiological health data as well as daily life activity data collected using wearable sensors, with a strong emphasis on the application of machine learning methods. In
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and monitoring. Develop methods for multimodal sensing, semantic understanding, information extraction, and digital twin integration using images, written reports, related sensor data. Execute numerical
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or geophysical sensors. Ability to collect, process, and analyze complex environmental datasets. Proficiency with scientific programming and data analysis software. Ability to prepare technical reports
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We are seeking a highly motivated Research Fellow to join our growing team developing next-generation electrical interfaces to diamond quantum sensors based on nitrogen-vacancy (NV) centers
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an excess of wild-type DNA. Compare and analyse amplification data from fluorescence-based with label-free photonics sensor readouts. Quantify assay performance using appropriate metrics, including time-to