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, manage research data and software, and assist in mentoring graduate and undergraduate students. HOW TO APPLY Applications should contain a cover letter briefly describing the candidate's research
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, and cell biological approaches to define receptor activation mechanisms and determine how extracellular immune signaling interfaces with intracellular SA signaling and systemic immunity. Potential
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particularly, finding proper references, creating schematic diagrams and compiling preliminary data for the proposal. Requirements Minimum Acceptable Education & Experience: PhD Knowledge, Skills & Abilities
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. Category 2 (30%) Data analysis from the experiments Category 3 (10%) Data publication; prepare peer-reviewed article. Requirements Minimum Acceptable Education & Experience: The position requires a PhD in
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presentations. The selected candidate will have an opportunity to work in a research-oriented laboratory equipped with state-of-the-art hardware and software tools, performing cutting-edge research related
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research partners, preparation of publications and presentations, and participation in a collaborative research visit to Texas A&M University. Expected Salary: $58,656.00 Required Qualifications: A PhD in
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. Minimum Qualifications Required PhD in microbiology, biochemistry, chemical engineering, or a related field. Demonstrated publication record of scientific findings in peer-reviewed journals. Experience
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. QUALIFICATIONS: The ideal candidate will have a strong foundation in dynamical systems, control theory, systems biology, and the theory of algorithms and computation. The candidate should possess a PhD in
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Classification Title: Post-Doctoral Associate in Chemistry Classification Minimum Requirements: PhD in Chemistry. Job Description: The Center for Molecular Magnetic Quantum Materials (M2 QM
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Postdoctoral Position in Computational Humanities to Research the Macroevolution of European Literat
Max Planck Institute for Empirical Aesthetics (MPIEA) | Frankfurt am Main, Hessen | Germany | 3 months ago, representing these influences through dynamic networks and directed graphs, and creating effective visualizations of large-scale literary networks. Using these inferred connections and networks, we will tackle