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We are seeking a Research Fellow to perform research on deployment of machine-learned models for health analytics on distributed IoT/edge/cloud systems using transprecise computing and contribute
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completion) relevant to research area (immunology). Expertise in flowcytometry and/or fluorescent microscopy. High level of analytical capability, especially in the understanding and analysis of large data
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Machine learning/AI based classifiers Proficiency in coding using R and Python and other similar languages High level analytical capability Ability to communicate complex information clearly Informal
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health sciences, social sciences, or economics Experience in qualitative research and/or health economic methods High-level analytical capability Ability to communicate complex information clearly Ability
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imaging High level analytical capability Broad understanding of next generation sequencing (NGS) technologies and demonstration of proven experience in analysis of bulk and single cell transcriptomic data
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microbial genetics and sequencing High level analytical capability Ability to communicate complex information clearly Ability to contribute to developing new protocols and techniques Ability to assess
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using flow cytometry to analyse in vivo immune responses High level analytical capability Ability to communicate complex information clearly Ability to contribute to developing new protocols and
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will need good communication skills, and will be able to work with and disseminate information to both academic and non-academic audiences. You will have a PhD in medical or bio-informatics, epidemiology
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will need good communication skills, and will be able to work with and disseminate information to both academic and non-academic audiences. You will have a PhD in medical or bio-informatics, epidemiology
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degree relevant to research area (health impact assessment) or equivalent qualifications High level analytical capability Ability to communicate complex information clearly including to non-academic