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- UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | about 2 months ago
. • Proven experience in one or more of the following areas: o Electrochemical biosensors o Bioelectroanalysis and bioelectronics o Wearable and implantable sensors o Microfluidic-based electrochemical
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at the earliest on 1st August, 2026. The position is funded by the Marie Skłodowska-Curie Doctoral Network (MSCA-DN), on “Understanding Lipid ImmunoMetabolism to treat disease” (UNLIMITED) within the Horizon Europe
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: - Proficiency in programming and Linux systems. - Strong background in telecommunications, networking, and/or computing. - Experiences in building wireless systems or experimental testbeds. - Familiarity with 5G
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micro energy and smart sensing devices to tackle long-term challenges like “Healthier Citizens” and “Net Zero Human Impact.” She has collaborated for over 20 years with Aitor on projects related
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in wireless networks, signal processing, and backscattering techniques. Understands 3GPP and UHF RFID protocol fundamentals Has strong programming skills (Python, C/C++, MATLAB). To accredit a level of
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Home EMA The European Magnetism Association Executive Board General Council Documents Membership EMA news Communication Social Networks Mailing Event Dissemination Rules All news EMA editorials
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-sensitivity cortisol sensor for biomedical applications and emotional monitoring Where to apply E-mail doctorats.industrials.recerca@gencat.cat Requirements Research FieldEngineeringEducation LevelMaster Degree
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | about 2 months ago
, Nanotechnology, or related fields. • Proven experience in one or more of the following areas: o (Bio)chemical sensors o Electrochemistry o Analytical chemistry o Wearable sensors (Attach publications or master's
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of Group/Project: The Nanobioelectronics and Biosensors group at ICN2 is focused on the development of cutting-edge sensors for various point-of-need applications. The group of Prof. Arben Merkoçi
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early detection is a need that needs to be addressed using advanced sensors. The candidate will apply machine learning and IA methods to anticipate the evolution of the discharges. This project aims