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Field
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Postdoctoral Associate | Mitochondrial Genomics | Lake Lab — Yale University, Department of Genetics
networking activities via the Yale Postdoctoral Association and Yale Office for Career Strategy. Qualifications Candidates should have or be close to obtaining a PhD in genetics, mitochondrial biology
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, Colloborative Governance, and Social Network Analysis. The position is part of the research centre-of-excellence CenSSUR, financed by the Swedish Civil Defence and Resilience Agency (MCF). The project studies
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to open-source releases Your profile - PhD in Meteorology, Physics, Computer Science, Environmental Sciences, or a related field - Experience with atmospheric models and geostatistical interpolation methods
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-throughput data, identify differentially expressed genes, explore protein interaction networks, and perform pathway and functional enrichment analyses. Responsibilities also include developing and optimizing
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contributing to academic publications and wider dissemination. The successful candidate will have a PhD, or be near completion of a PhD in a discipline relevant to high-stakes regulated domains, such as
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imaging data (e.g., CellProfiler, convolutional neural networks).•Knowledge of chemo-informatics and drug discovery.•Strong practical statistical skills (batch effects, confounders, experiment design). You
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of undergraduate and postgraduate students. About you We are seeking an exceptional Postdoctoral Research Associate in Linguistics who has: a PhD in Linguistics completed a comprehensive grammatical description of a
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Participation in the publication of the journal "Forum Islamic-Theological Studies" This is part of your personality: Excellent German language skills (at least C1 level) are essential Completed doctoral/PhD
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(CML-IE) and Environmental Biology (CML-EB). Presently, about 150 fte (including postdocs and PhDs) are employed at CML. CML further collaborates with TU Delft and Erasmus University in the Leiden-Delft
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The Pluskal lab at IOCB Prague combines cutting-edge experimental (e.g., LC-MS, metabolomics, RNA-seq) and computational (e.g., bioinformatics, molecular networking, machine learning) approaches