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Field
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Research Assistant for Applied Mathematics - Responsibilities - Analyze a dataset of case law in the domain of worker classification and develop algorithms to predict judges decisions based
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master’s degree in related fields (computer science, electrical engineering, or computer engineering) Previous experience in Python programming Experience implementing machine learning algorithms in python
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | 20 minutes ago
circuitry of the vertebrate brain gives rise to the computational algorithms that animals use to solve real-world behavioral problems. We study this question in the larval zebrafish, where we can combine
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comparison of predictive algorithms—such as Random Forest and LSTM neural networks—for use in genetic material recommendation systems. Working as part of Camcore’s data science team, the selected candidate
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, require limited supervision and high-level of independence are highly desirable. About the lab and St. Jude: Our lab focuses on computational methods development and large-scale genomic/genetic analysis
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candidate with expertise in statistical learning and machine learning, both theoretical and computational. Minimum Education and Experience Ph.D in a related field. Preferred Education and Experience Other
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. Uses appropriate algorithms, logic, and data structures to solve problems and promote code reusability 4. Writes well organized, documented, and readable code 5. Uses appropriate revision control
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genetic knockouts in yeast and mammalian cell lines, and protein purification. Job Responsibilities: 35%: Computational algorithm development and data analysis 35%: Design and conduct experiments with yeast
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). Applicants with a PhD in a quantitative field (computational biology, bioinformatics, systems biology, genetics/genomics, statistics, mathematics, computer science, or related fields) are encouraged to apply
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systems, multi-function radar, AI/ML algorithms rely on high performance digital signal processing and real-time computing to provide high-fidelity results in an actionable timeframe. The ARRC intends