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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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technical skills in next generation sequencing, including library preparation and bioinformatics analysis. Experience in developing bioinformatics pipeline and maintaining computer server would be
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with mouse genetics, molecular biology (including functional genomics) and bioinformatics (including UNIX, R and Python for single cell analysis). You will be highly motivated, current with
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techniques. -Experience analyzing omics data using bioinformatic tools. -Proven record of publishing first-author peer-reviewed papers. -Experience working with honey bee biology and/or beekeeping practices
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part of the project team. Applicant requirements Ph.D. in bioinformatics, proteomics, drug design and development, genomics, mathematics, computer science, or related fields Complete CV Short research
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(renewable, contingent on performance and funding) will work under the mentorship of Dr. Fei Ye on to conduct quantitative research on development and application of statistical/bioinformatic methodology
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. They should have solid knowledge of chemistry and biology, and an excellent command of spoken and written English and Chinese. Experience in bioinformatic data analysis including microbiome, virome and
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evolutionary/quantitative/population genetic analyses on existing large datasets. Apply and develop bioinformatic pipelines to analyze diversity data, especially in the context of pan-genome resources. Work
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. Applicants should possess a Ph.D. degree in Biomedical Engineering, Biochemistry, Cancer Immunology, Genomics, Bioinformatics, or a related field, and demonstrate exceptional experimental, writing, and