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is to detect cognitive strategies in single-trial EEG data. In very broad terms, we will use the HMP method (https://github.com/GWeindel/hmp ) to discover cognitive operations in existing data, label
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 2 months ago
, experience with a priori power analysis and (automated) data processing are desirable. Main Research Field: Statistics Where to apply E-mail [email protected] Requirements Research FieldMedical
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https://hr.northeastern.edu/benefits/ for more information. All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color
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big data. Among the key duties of this position are the following: Participate in lab meetings, research-in-progress seminars, data analysis, and presentations at conferences. Participate in the ACTIVE
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planetary atmospheres. The Section also initiates and manages a wide range of related modelling, software and hardware R&D activities. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s
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engineering and protein biochemistry is essential. Experience in -omics methods, as well as in protein production and characterisation (FPLC, WB, etc.), is required. Skills in the analysis of omics data and the
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on enhancing child and adolescent mental health care. Experience in working with longitudinal data sets and knowledge of advanced statistical methods for analysis of longitudinal data. Experience in research
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computing (Linux) environments, including shell scripting. Strong programming and data analysis skills (e.g., Python, Fortran, R). Demonstrated ability of scholarly output (peer-reviewed publications and
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methodologies to support interdisciplinary cancer research programs, including magnetic resonance imaging (MRI), optical imaging, micro-computed tomography (micro-CT), photoacoustic imaging, and image analysis
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. Proficiency in R and/or Python and experience working in Unix/Linux computational environments. Familiarity with statistical methods for genomic data analysis, including differential expression, clustering