148 parallel-processing-bioinformatics-"Multiple" Postdoctoral research jobs in Germany
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-08187-1 Your Profile: Master and PhD in biology, genomics or bioinformatics Strong background in data science or machine learning (deep learning, statistical modeling, or large-scale data analysis a plus
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aromatic nanobelts. Your profile: We are looking for experimentally skilled candidates, ideally experienced in multiple-step organic synthesis The candidate needs to have a PhD degree in Chemistry (with a
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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culturing, integrating multiple automated subsystems with image-based machine learning models. Our objective is to enable robotic decision-making through machine learning, paving the way for a standardized
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opportunity to address a broad variety of fundamental and applied ecological questions in fields like metacommunity theory, time series analyses, multiple stressors responses, invasive species, ecological
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and skills: You hold a PhD in Bioinformatics, Computational Biology, Genomics or a related field. You bring proven expertise in deep learning and statistical modelling of biological data. You have
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Proficiency in bioinformatics, single-cell omics, or advanced imaging analysis Familiarity with functional readouts (e.g., MEA, calcium imaging, electrophysiology) is a plus Competitive applicants must have
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on Clostridium carboxidivorans and Clostridium ljungdahlii, for which we have already established robust genetic and process engineering platforms. The following publications illustrate the potential and direction
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Hospital Bonn, the position will be affiliated with a newly established junior research group focusing on early detection of Alzheimer's disease using multiple layers of omics data and statistical modeling
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ljungdahlii, for which we have already established robust genetic and process engineering platforms. The following publications illustrate the potential and direction of our work: Lauer et al. (2022): Metabolic