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. Research in the lab is highly multidisciplinary and quantitative, requiring development and use of cutting edge computational modeling and statistical analyses (including machine learning and artificial
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player and great collaborator Strong interest in interdisciplinary work at the interface between neurodegeneration, modeling, screening and machine learning Prior experience in iPSC modelling and CRISPR
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learning university. In this competition, experience in research and/or development in Large Language Models (LLM) and their respective applications is valued. Where to apply Website https
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biofoundries, fostering sustainable industrial biotechnology across the bioeconomy sectors. The lab combines synthetic biology, machine learning, and biosensor and pathway dynamic regulation design to produce
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. Excellent written and verbal communication skills, with the ability to work effectively with diverse groups and provide high-level customer service. 3. Demonstrated proficiency with computer applications
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frameworks. Familiarity with machine learning or AI methods applied to imaging. Research Data Management and documentation practices Statistical Analysis & Experimental Design Technical Communication (reports
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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separation on commercial recordings and extracting audio features (onsets, pitch, harmony, dynamics); curating datasets; and integrating machine learning approaches to complement rule-based methods. For more
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outcomes. General computer skills and ability to quickly learn and master computer programs, databases, and scientific applications. Ability to work under deadlines with general guidance. Excellent
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of machine learning What We Offer: On the basis of full-time employment (40 hours/week) the minimum salary in accordance with the collective agreement is € 5,014.30 gross per month (14 x per year, CA Job Grade