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resources. Maintains awareness of subject and disciplinary repositories of potential interest to the OU research community. Maintains awareness of tools and algorithms for computationally centered, data
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the neural mechanisms underlying goal switching and behavioural strategy selection, linking algorithmic theories of behaviour to defined microcircuits and pathways. The position will employ a multidisciplinary
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biomedical data science, developing new methodology and scalable algorithms, and collaborating with interdisciplinary teams at Duke. Duke is an Equal Opportunity Employer committed to providing employment
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, and digestive diseases, to genetics, genomics, neurosciences, and women's health. You can continue your career journey with us! The Slomka Laboratory focuses on developing innovative methods for fully
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optimisation algorithms for quantum routing using genetic algorithms (GA), ant colony optimisation (ACO), and particle swarm optimisation (PSO), optimising cost functions subject to entanglement fidelity
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simulation software. Develop algorithms and techniques that reinvent signal understanding and processing. Collaborate closely with the tight-knit members that make up the Simulation Team and collaborate
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via bitbucket). Backup code on bitbucket and oversee the revision of the code to integrate with other algorithms. Algorithm development initially will involve solving problems such as: (1) base calling
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analyses Skills and requirements Excellent master and doctoral degree in Computational Science/Bioinformatics Strong background in biological fundamentals, including genetics and epigenetics Expertise in
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Genetics (GMG) initiative in collaboration with the Global Methane Hub and the Bezos Earth Fund. The global program with more than 50 partners across 25 countries aims to accelerate genetic progress in
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experimental molecular biology and data analysis. Doctoral candidates can specialize in genomic and molecular biology techniques, as well as in algorithms, statistics, and artificial intelligence for molecular