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Postdoctoral Research Associate I, Translational Cardiovascular Research Center (Phoenix)

University of Arizona · arizona.edu
PhoenixEntry level
Apply on University of Arizona’s site

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The job in short

Postdoctoral research in translational cardiovascular research.

PythonMachine learningCompliance

Details

Found
28 d ago · posted 2026-01-05
Location
Phoenix, AZ, US

Full description

Develop and maintain detailed records of experiments, analyzing and writing findings. Assist with preparation of grants and manuscripts. Present manuscripts, oral presentations, posters, and research findings at national and international conferences. Plans, coordinates, and conducts scientific research requiring judgment in the independent evaluation, selection, and substantial adaptation and modification of standard scientific techniques. Serves as principal investigator, as appropriate, on sub-projects of complexities consistent with the above criteria. Generate new ideas and projects for development. Designs, performs, and/or oversees experiments and data collection to ensure data integrity, quality control, and protocol compliance. Collects, analyzes, and interprets data. Prepares statistical and narrative reports and/or graphs as appropriate to the specific position. Prepares manuscripts for publication. Presents research results to scientific conferences and other groups. Share supervisory responsibility for research technical staff including graduate and undergraduate students. Attend regular group meetings; manage, maintain, and order laboratory equipment and supplies; and respond to administrative requests and procedures. Knowledge, Skills Abilities: Strong computational skills in programming languages (e.g., Python, R, Perl) and software tools for bioinformatics analysis. Excellent communication skills (both written and verbal) for presenting research findings and writing grants. Proficiency with bioinformatics databases (e.g., Ensembl, NCBI, UniProt) and tools (e.g., BLAST, Bowtie, SAMtools). Knowledge of statistical methods and machine learning techniques for biological data analysis. Strong problem-solving skills with attention to detail and data integrity.

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