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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a
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contribute to overall lab operations. The applicant will be a collaborative, impact-focused problem solver who wants to be part of a dynamic team. Learn more about the innovative work led by Dr. Don Ingber
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interest and expertise in neurohistology, stereology, and other microscopy analysis techniques. Additional projects and training opportunities can be tailored to suit the candidate's goals and interests
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Math, or related field. Strong coding/computing skills. Familiarity or strong interest in the analysis of pathogen genomic/molecular data Additional Qualifications Special Instructions Required documents
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contribute to overall lab operations. The applicant will be a collaborative, impact-focused problem solver who wants to be part of a dynamic team. Learn more about the innovative work led by Dr. Don Ingber
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Math, or related field. Strong coding/computing skills. Familiarity or strong interest in the analysis of pathogen genomic/molecular data Additional Qualifications Special Instructions Required documents
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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive
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status, disability, genetic information, military service, pregnancy and pregnancy-related conditions, or other protected status . Create a Job Match for Similar Jobs About Harvard University Harvard
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, national origin, ancestry, age, protected veteran status, disability, genetic information, military service, pregnancy and pregnancy-related conditions, or other protected status. Create a Job Match for
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to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service, pregnancy and