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to disentangle co-occurring conditions using multi-omics data in Down syndrome. The position will be jointly mentored by Dr. Casey Greene in the Department of Biomedical Informatics and is funded by the NIH
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biology and in vivo modeling. Knowledge, Skills and Abilities: Proficiency with flow cytometry Excellent communication skills. Excellent writing skills Demonstrates the proficiency in computer software
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integrate genomic data, microscopy data, and mouse behavioral data Present research findings in group meetings Publish research findings, assist with grant writing, and present work in conferences It is not
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supervision from Dr. Brice McConnell, Dr. Ashis Biswas, and Dr. Nicholas Dwork. Professional Field: Machine Learning & Data Science Biomedical Sciences & Neuroscience Computational Biology & Bioinformatics Key
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at the time of hire. PhD in Computer Science, Artificial Intelligence, Computational Linguistics, Machine learning, Computer Engineering or related fields Preferred Qualifications: Experience in developing and
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single-cell transcriptomic data. The candidate should be proficient in, or highly motivated to learn cancer data science, machine learning, and high throughput sequencing analysis. Successful applicants
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Campus. The appointment will be for a two to three-year period. The main emphasis of this position will be working in the research areas of genomics, cancer biology, and patient-derived organoids
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, including design of experimental setup, data generation, data interpretation, and manuscript writing, with the following key responsibilities: Wet lab responsibilities: Conducting molecular biology
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verifying accuracy of research data; coordinating various meetings with study staff, collaborators, and other stakeholders, including community partners as needed; and data management. Additionally
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. The fellow will conduct research-related activities, which include day-to-day research operations, clinical trials management, data management and analysis, supervision of graduate and undergraduate research