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Field
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/bayesian/deep-learning analyses, with functional validation in spruce via CRISPR-Cas9 and nanoparticle delivery. The postdoc will join Professor Nathaniel R. Street’s team at UPSC, working closely with
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, or related areas, fields or environments. We expect experience and competences in one or more fields of research on late working life; labour markets; public, branch and employer policies; lifelong learning
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. You will be responsible of synthesizing results into compelling figures, making and delivering oral presentations, writing manuscripts, and mentoring students. You will be expected to learn basic R
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, Micro-C/Hi-C, BS-Seq/EM-Seq), massively parallel enhancer assays (ATAC-STARR-seq), and comparative/bayesian/deep-learning analyses, with functional validation in spruce via CRISPR-Cas9 and nanoparticle
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of training in higher education teaching and learning. The purpose of the position is to develop independence as a researcher and to create the opportunity for further development. The postdoctoral position
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statistics and machine-learning–assisted approaches, in close interaction with data science collaborators Active collaboration across disciplines spanning spectroscopy, soft matter and nanomaterials
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metaproteomics approaches Analyzing large-scale multi-omics and clinical datasets to investigate individual metabolic responses to diet. The work includes applying advanced statistical and machine learning methods
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Communication at the Department of Communication and Learning in Science, and a member of our graduate school Communication and Learning in STEM. The division’s research is situated at the intersection
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are self-driven, eager to learn, and possess good analytical problem-solving skills Programming skills in Python or Matlab. You are expected to be somewhat accustomed to teaching, and to demonstrate
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skills. Ability to teach in English. Willingness to travel and perform experiments outside of University West if needed Additional Information: A postdoc appointment is a time-limited position primarily