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metagenomics and Oxford Nanopore Technologies sequencing. Large experience in bioinformatics, machine learning and high-performance computing in relation to microbial metagenomics and analysis of horizontal gene
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electroluminescence and photoluminescence imaging, preferably daylight and field-based methods. Proven skills in data analysis, image processing and machine learning. Experience with PV performance modelling, power
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method development and DNA library preparation for Oxford Nanopore sequencing. Large experience in bioinformatics, machine learning and high-performance computing. Furthermore, excellent written and oral
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Postdoc who, in addition to the desired expertise stated above, have the following skills and qualifications: A PhD degree in bioinformatics, machine learning, computational biology, statistical genetics
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metagenomics and Oxford Nanopore Technologies sequencing, wet lab method development and DNA library preparation for Oxford Nanopore sequencing. Large experience in bioinformatics, machine learning and high
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, bioinformatics, aging biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and
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. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and process-based radiative transfer models
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academic or industry leadership roles. Your profile Applicants should hold a PhD in Computer Science, Electrical Engineering, Computer Engineering, Telecommunications, or a similar field, with a strong
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, glacier speedup, and ice-ocean interaction. Candidates will work with satellite altimetry, velocity datasets, and climate data to quantify ice sheet mass balance and dynamics. Applicants should hold a PhD
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, mechanical and durability testing, and integration with advanced machine learning models. The postdoc will collaborate closely with CEBE’s parallel work packages. Experimental and analytical data generated in