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data accordingly to research specifications. Uses a computer terminal to input and retrieve data and to generate reports. 3. Processes and summarizes data using scientific or statistical techniques
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specifications. Uses a computer terminal to input and retrieve data and to generate reports. 3. Processes and summarizes data using scientific or statistical techniques. Assists in data interpretation and analyses
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to research data. Codes data accordingly to research specifications. Uses a computer terminal to input and retrieve data and to generate reports. 3. Processes and summarizes data using scientific or statistical
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Computational Biology, Machine Learning and Deep Learning for Computational Biology, Computer Science, Applied Physics and Mathematics, or a related field. - Strong background in protein modeling, structural
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independent research. The successful candidate will work in a team of fellow trainees in the lab. Learn more about the Tang lab at https://www.steventanglab.com. The Tang lab is committed to training
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topics include, but are not limited to (i) developing statistical and machine learning methods for study designs and decision-making in early detection of pancreatic cancer (ii) establishing strategies
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professional deliverables ● Experience with causal inference, machine learning, and artificial intelligence is desirable ● Experience with clinical, EHR, or biobank data analyses is desirable
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methylation sequencing, single cell DNA methylation, and single cell transcriptome • Perform machine learning/deep learning analyses; and delivering analytical results. • Develop workflows for multiple
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strong background in machine learning and a keen interest in neurobiology. Previous experience in topics such as gene-regulatory networks, xQTL analysis (splicing, expression, chromatin accessibility
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in candidates with interest in algorithms, blockchains and cryptocurrency, causal inference, game theory, learning, machine learning, market design, and networks, but all subjects at the intersection