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publications see here: https://www.scilifelab.se/researchers/stefanos-stagkourakis/ Essential technical expertise (Required) This position is intended for candidates who can immediately operate at a high
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professor plus an international tutor of the RTG Description of the PhD topic: Innovative Air Mobility (IAM) networks are currently being designed in cities worldwide. These networks rely on electrically
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: • Advanced gene expression platforms (RNA-seq, microarrays, high-density qRT-PCR) • Flow cytometry instruments • Mutational profiling platforms (DNA-seq) • Exosome analysis tools (Nanosight) • Fully equipped
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-resolution, high-density 3D seismic survey was acquired in summer 2025 as a baseline for future monitoring. Job description You will work at the interface of reflection seismology, geophysical monitoring, and
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density structure of the star-forming interstellar medium”, funded by the Swedish Research Council (PI: J. Kainulainen). In this project, we combine novel observational data, such as Gaia-based dust density
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? We currently have a job opening for a: University Assistant (must hold a Doctorate/Ph.D. degree) for a full-time, six-year position Organizational unit: Institute for Machine Learning Entry date: 02/02
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. Unfortunately, around 50% of these individuals are unable to benefit from current or emerging treatments such as gene or stem cell therapies, pharmaceuticals, or retinal prostheses. Although cortical
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for power electronics using a vertical geometry to gain in current density and accompany voltage rise. This 48-month project began in 2022, and is coordinated by CEA (Grenoble) and the AMPERE laboratory (Lyon
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2020 and 2040. With the current technology, 10% of those artificial shoulder implants will fail within the first 10 years of service, mainly due to soft tissue failure, infection, and implant loosening
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optimization procedures, and bone-quality assessments. Analyze multimodal datasets including radiographs, CT imaging, gait analysis, prosthetic sensor data, and bone-density measurements. Build robust data