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REQUIREMENTS Penn State Scranton is currently accepting applications for part-time research assistants at the Sustainable Communities Lab. Read more about Sustainable Communities Lab here: https://nonnasorokina
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. The postdoc will play a central experimental role in the project and work closely with a dedicated postdoc supporting advanced computational analysis and interpretation of data. The position offers substantial
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The Department of Surgery's Division of Vascular Surgery is seeking a Data Analysis Assistant/Specialist to collaborate on research within Dr. Craig Weinkauf's lab. This individual will work closely
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with data analysis, and contribute to the overall efficiency and safety of the laboratory. This position will have hands-on experience in molecular and cellular biology research. Job Description: Job
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development of existing image and data analysis tools -performance characterization using various types of samples (calibration samples, model systems, biological samples and/or nanomaterials) -participation in
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mechanisms that regulate dopaminergic neuron vulnerability in ageing and Parkinson’s disease, integrating human stem cell–derived neuronal models, in vivo studies and translational human tissue analysis
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, Medical Image Analysis and Clinical Big Data Analysis research, or a related discipline A successful candidate will have ability to apply for research grants and teach graduate courses Preference will be
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the world, which we are achieving through the talents and endeavour of every employee. Our culture empowers people to achieve this aim and to collectively, and individually, make a real difference. The role
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participating in short term practical work experiences (internships and co-ops) that are relevant to their vision and skill level. Course content includes areas such as: self-assessment, industry analysis and
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methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team orientation excellent