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Field
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spatial and temporal data analysis using advanced machine learning technologies. The successful candidate will become a part of an interdisciplinary team working to develop machine learning techniques
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 13 hours ago
advanced in silico prediction algorithms, analyzing machine learning approaches for toxicity pattern recognition, and participating in developing standardized computational frameworks for regulatory
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to demonstrate skills on Data Analytics and Machine Learning, in particular on distributed ML. Must have very good programming competence in Python, Java, C/C++ or equivalent Fluent oral and written communication
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focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute
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Informatics and edge intelligence etc. Must have documented significant Knowledge/Research Background, or Must be able to demonstrate skills on Data Analytics and Machine Learning, in particular on distributed
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protein coding genetic association data with functional and machine learning-derived features 4. Developing methods to characterize the genetic architecture of autism Salary and Benefits This position is
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years. During the NLM T15 sponsored Postdoctoral Fellowship, you will study and perform research in Biomedical Informatics, working on one or more of the following: Artificial Intelligence / Machine
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, modeling machine learning, and scientific simulation Ability to work well in an interdisciplinary environment, and to collaborate with experimentalists Strong oral and written communication, data
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(EHR), health information exchanges, and data analysis software. Experience with health IT innovation, including working with artificial intelligence, machine learning, telemedicine, or mobile health
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towards better understanding what replication can mean for qualitative research. Last but most topically, the theme of replication raises a host of questions in relation to machine learning and artificial