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at the University of Amsterdam and will lead the development of advanced computational data analysis methodologies. Your primary goal is to connect different levels of the degradation pathway to the parent molecule
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projects integrating omics, clinical and medical imaging data, contributing to biomarker identification and the development of computational approaches for healthcare. Key responsibilities include analysis
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contribute to high-impact research on machine learning related to the analysis of IoT data in the form of multivariate time series. The DESS group is part of Department of Computer Science that belongs
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
supervision of Dr. Hanan Salam on the: Development of an Augmented Smart Classroom for Personalized Learning (SmartClass) serving as a test-bed for the collection and analysis of students and professors data
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cementitious materials and concrete durability; experience designing and supervising experiments; familiarity with LCCor alternative binders; strong data analysis and publication record; effective communication
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resident to work remotely. The Postdoctoral Scholar will play a key role in designing and implementing research protocols, leading data collection and analysis, producing peer‑reviewed publications, and
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novel methods across evolutionary analysis, mathematical modelling, micro-scale experiments and 3D printing. You will have a PhD (or close to completion) in biophysics, bioengineering, mathematical
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27 Mar 2026 Job Information Organisation/Company Instituto de Neurociencia Avanzada de Barcelona Research Field Neurosciences » Other Researcher Profile Recognised Researcher (R2) Positions PhD
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and image analysis. You are familiar with molecular biology techniques and working with multi-modal datasets. You are interested in integrating morphological, molecular, and genetic data to address
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ExperienceNone Additional Information Eligibility criteria PhD in condensed matter physics or materials science. Strong background in magnetism, spintronics, and/or ferroelectricity. Experience in the growth