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, Skills and Experience: Completed a PhD in a relevant field (e.g., synthetic biology, bioengineering, genetics, molecular biology, evolutionary biology, computational biology and AI, cell biology, genomics
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Biology, Evolutionary Biology, Microbiology, Epidemiology, Biostatistics, Applied Math, or related field. Strong coding/computing skills. Familiarity or strong interest in the analysis of pathogen genomic
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 4 hours ago
optimization algorithms and/or machine learning models for complex systems or real-world applications Experience with large-scale optimization or deep learning systems is highly desirable Duties and
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using Python, R, Java and C/C#/C++, as well as competence in mathematics including probability, statistics and algorithms. Keen interest to support research and academic project work, with demonstrated
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computational research projects is required for the proposed research. Expertise in population or evolutionary genetics is preferred but not required. Required skills: · Experience with Python · Experience with
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of the following areas: - Quantum computing-specific: o Error-correcting codes o Lattice surgery o Surface codes o Resource estimation o Homology o Circuit design/algorithms - Mentorship - Open-source software
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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
interface to humans with varying expertise in real-world responsible AI scenarios. The successful candidate will design and develop new AI algorithms and systems, engage with a dynamic research group within
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well as competence in mathematics including probability, statistics and algorithms. Keen interest to support research and academic project work, with demonstrated ability in developing software solutions to technical
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of the call Past experience in AI algorithms Past experience in Research Projects EVALUATION CRITERIA The selection will be based on the following criteria: Academic record (50%) Past Experience in AI