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: Bachelor’s degree in bioinformatics, Biostatistics, Computational Biology, Data Science, Computer Science or related field A combination of education and related technical/paraprofessional experience may be
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Bioinformatician at the intermediate or senior level. The Breuss laboratory is focused on employing and developing statistical machine learning, bioinformatic algorithms, and related approaches for the detection
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early development of the placenta, and a basic understanding or willingness to learn bioinformatics is desired. The candidate should be proficient in, or highly motivated to learn complex 3D culture
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to disseminate the study results. Collaborate with and support Principal Investigators (PI) and other stakeholders in the area of bioinformatics and data analysis. Assist with the design and development of major
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activities, participate in project meetings relevant to the design, development, implementation, and maintenance of data management system Perform scientifically rigorous data management and bioinformatic
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learn new research skills based on your interests. These may include performing and analyzing high-throughput drug screening experiments, bioinformatic analyses (single-cell, metabolomics and proteomics
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, cardiology, emergency medicine, pharmacotherapy) training or equivalent clinical training Three (3) years in pharmacy and/or data management and bioinformatic analyses experience Preferred Qualifications: Four
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Cytometry Innate immune system experience Molecular biology Biochemistry Metabolism Cell culture Bioinformatics Knowledge, Skills and Abilities: Ability to communicate effectively, both in writing and orally
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, bioinformatics, microscopy, statistical analysis, writing, presentation Subject-matter interest: immunology and/or neurobiology How to Apply: For full consideration, please submit the following document(s): 1
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statistical genetics and bioinformatics-related projects in the lab. Contribute to mentorship and training, developing educational materials and guiding lab members on statistical genetics and computational