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. The candidate will apply a suite of statistical and physical models for integrating observations of different accuracies, improving predictions of future hazards. The work will further include research, writing
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and security challenges, build sustainable solutions, and provide expert perspective on using AI. Required Qualifications - PhD in computer science, statistics, data analytics, business administration
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analytical stills, including the use of statistical software (R, JMP, SAS, etc.) Preferred Qualifications N/A Overtime Status Exempt: Not eligible for overtime Appointment Type Restricted Salary Information
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· Ph.D. degree in Computer Science, Electrical and Computer Engineering, Computational Biology, Bioinformatics, Statistics, Mathematics, Biophysics, Physics, Chemistry, Biology or related fields. · PhD
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neural receiver, from reflecting intelligent surfaces (RIS)/integrated sensing and communications (ISaC) to network design using O-RAN, from statistical learning theory to software defined radio (e.g
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and presenting at professional conferences. • Strong understanding of experimental design, data collection, and statistical analysis. • Ability to work both independently and collaboratively in
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publications. • Strong understanding of experimental design, data collection, and statistical analysis. • Ability to work independently and collaboratively in an interdisciplinary research environment
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collaboratively in interdisciplinary teams. Preferred Qualifications - Experience with stakeholder engagement or extension programming. - Familiarity with statistical software (e.g., SPSS) and qualitative analysis
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Qualifications • Ph.D. in fisheries, biology/ecology, statistics, or related fields. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility
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- Significant statistical analysis experience with multilevel and/or longitudinal data - Strong conceptual and written communication skills Preferred Qualifications - Staff and graduate student supervision