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Field
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, or MATLAB) are required. Knowledge in one or more of the following areas is desirable: biomedical imaging, biomedical optics, computer vision, bioinformatics, single-cell profiling technologies, spatial omics
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Develop and apply machine learning techniques and statistical analyses, including digital twin methodology, to fit and validate prediction model. Perform quality control and imputation of genotype and
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considering the following criteria: Prior relevant work or industry experience Education level to the extent education is relevant to the position Unique applicable skills Academic Discipline To learn more
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-cell genomics, transcriptome imaging, optical electrophysiology, and machine learning to study how the genome builds a brain across spatial and temporal scales. Key questions we aim to address include: 1
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, skills and abilities: -Proficiency in image analysis using machine learning methods. Continued employment in this position is contingent upon availability of funds. Please attach the following to completed
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survival data using longitudinal features, and (6) machine learning and deep learning for analyzing time-to-event outcomes, or (7) radiomics and medical imaging analysis. Required Qualifications: We seek
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areas. At least one first-author publication, accepted or submitted Strong analytical, organizational, and record-keeping skills Proficient computer skills, including MS Office and research software
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principals to problem solve work. ● Ability to maintain detailed records of experiments and outcomes. ● Ability to quickly learn and master computer programs, databases, and scientific applications
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analysis of atmospheric numerical model output (e.g., WRF, PALM, SAM) Experience with machine learning and artificial intelligence techniques Experience with predictive modeling Environmental, Health
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studies. Proficiency in relevant computational tools and statistical methods. Experience with machine learning in large datasets. Interest and motivation to work in a multidisciplinary team. Ability to work