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manner. Collaborative Innovation: Lead and participate in collaborative initiatives aimed at developing novel computational tools, algorithms, and models that address critical challenges in drug discovery
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biological samples' 3D structure and molecular identity. At iBIO, we bring together cutting-edge science from biology, chemistry, engineering, and computer applications. Our overarching aim is to obtain a
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analyzed. The tensor model structure estimated by suitable optimization algorithms, such as that recently developed in [GOU20], will be considered as a starting point. • Exploiting data multimodality and
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on FNR’s prestigious PEARL program, and has the option for an affiliated professorship. Both LIH and DFKI pledge their full commitment to ensuring that this new position becomes a cornerstone in the
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of tumour growth and metastasis. Project outline The Computational Biology Group applies a range of computational and Machine Learning approaches to the interpretation and analysis of complex multimodal
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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(morphological patterns), based on the experts’ knowledge. Then, tools like Procrustes analysis, linear dimensionality reduction (PCA) and standard clustering algorithms are employed. A first objective of our
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algorithm Maintain a lab notebook of raw data and organize data for analysis by senior lab members Keep detailed records Qualifications Bachelor’s degree in Biology, Neuroscience, Psychology, Biology
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of multi-omics data sets generated with innovative high-throughput technologies used in Research Sections I and II (e.g. sensory, metabolome, proteome, and transcriptome data) by using efficient algorithms
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challenges, encompassing both fundamental and applied research, from the development of algorithms, tools, and frameworks that advance scientific discovery to methodologies that utilise computational