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algorithms and data structures, and solid programming skills. A background in one or more of: machine learning, reinforcement learning, combinatorial optimization, operations research, or distributed systems
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. Experience in bioinformatic WGS data analysis and interpretation from bacterial isolates for AMR surveillance and/or genomic epidemiology. Proficiency in relevant bioinformatics tools and programming
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with command-line computing, for example in a Linux environment Experience with scripting or statistical programming in a language such as Python or R Some hands-on experience with microbiological
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background and interest in AI systems, embedded intelligence, edge computing, machine learning, or related areas. Strong analytical and mathematical problem-solving skills. Experience with programming