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

The ideal candidate should have a strong background in algorithm development, transcriptomics, sequencing data processing, and/or applied machine learning. The individual will develop novel algorithms to analyze large and complex biomedical data sets and contribute towards research and research-related service in translational cardiovascular research. The Postdoctoral candidate will benefit from the interaction with a dynamic and interdisciplinary environment at the University of Arizona College of Medicine - Phoenix.

The University of Arizona College of Medicine – Phoenix anchors the 28-acre Phoenix Bioscience Core in the heart of the Valley of the Sun. The College inspires and trains individuals to become exemplary physicians, scientists and leaders who are life-long learners and inquisitive scholars. The Phoenix Biomedical Campus embodies the University’s priorities of engagement, partnership, innovation, and synergy in its world-class academic and research initiatives, with clinical facilities throughout Greater Phoenix.

Outstanding U of A benefits include health, dental, and vision insurance plans; life insurance and disability programs; paid vacation, sick leave, and holidays; U of A/ASU/NAU tuition reduction for the employee and qualified family members; retirement plans; access to U of A recreation and cultural activities; and more!

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• 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.

• PhD in biomedical science, molecular biology or vascular biology, biochemistry, physiology or
  related field is required.

• Experience in molecular biology.
• Experience with large-scale data analysis (e.g., next-generation sequencing, proteomics, transcriptomics, metabolomics).
• Proven track record of scientific publications in peer-reviewed journals.
• Collaboration experience with experimental biologists and interdisciplinary teams.
• Experience with high-performance computing environments (e.g., Linux, cloud computing, cluster management).

College of Medicine-Phoenix, Office of Human Resources

Talent@arizona.edu

Application: The online application should be completed in its entirety. Blank or missed information may be considered an incomplete submission.

Letter of Interest: Should clearly indicate how your skills and professional employment experience meet the Minimum and the Preferred qualifications (if applicable).