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Field
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responsibilities of the position include: - Single-cell and single-nucleus RNA-seq analysis - Spatial transcriptomic data analysis - Designing novel statistical methods for single-cell and spatial transcriptomic
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for presenting your work at international conferences and workshops. The successful candidate should hold, or be close to completion of, a PhD/DPhil in a quantitative discipline, for example statistics
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or creating geo-demographic profiles Excellent statistical knowledge including working with spatial statistics and the use of statistical packages such as Stata and/or R Experience of working with a diverse set
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evaluate crop performance and soil quality among different on-farm experimental set-ups in Germany and aims to optimize different statistical solutions for long-term, landscape and monitoring experimentation
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editing strategies and to select disease variants. Applicants should hold a relevant PhD (or be close to completion - thesis submitted at time of application) in Computational Biology, Bioinformatics
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statistical skills; Collaborate with scientists with different backgrounds; Write scientific peer-reviewed manuscripts; Participate in regularly scheduled meetings with PI and Co-Is. Required Skills PhD
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statistics. You will be responsible for establishing a large health record linkage cohort to enable research degerming whether conception by assisted reproductive technology (ART), compared to conception
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postdoctoral research associate. This is a full-time, 12-month position, with an anticipated funding period of at least two years (pending annual review and funding availability). This opportunity is supported
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. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . JOB DESCRIPTION AND POSITION
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Leadership and co-supervision Requirements: Completed a PhD in a quantitative discipline (statistics, mathematics, computational biology, data science). Strong programming skills (R preferred