"Postdoctoral Research Associate I or II, Data Science (Center for Innovation in Brain Science - CIBS)"

Position Highlights

The Center for Innovation in Brain Science (CIBS) is seeking a research scientist to lead and implement data-driven research focused on advancing Precision Menopausal Hormone Therapy (P-MHT) for women worldwide. Integrate and analyze large-scale human datasets, including electronic health records, claims data, and omics profiles, to identify treatment response patterns, subtypes, and critical intervention windows that reduce Alzheimer's risk Disease (AD) risk. This position will involve applying machine learning, deep representation learning, and real-world data modeling to stratify risk and optimize MHT formulations. The candidate must thrive in a multidisciplinary, fast-paced research environment and work independently and collaboratively across teams.

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

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Duties & Responsibilities

• Conduct integration, analysis, and interpretation of large-scale human health datasets (e.g., UKBioBank, WHI, All of Us) using statistical and artificial intelligence/machine learning techniques.
• Develop and implement machine learning models, including unsupervised clustering and deep learning approaches, to identify precision treatment profiles and disease trajectories.
• Analyze research data and provide interpretations.
• Prepare manuscripts for publication and assist with grant applications.
• Present research findings at group meetings and national and international conferences.
• Graduate and undergraduate mentorship.
• Work collaboratively with other members and laboratories in CIBS.
• Additional duties as assigned.

Knowledge, Skills, and Abilities:

• Deep understanding of data science, AI/ML, and bioinformatics applications in biomedical research.
• Experience working with large EHRs, claims, or omics datasets.
• Ability to conduct research independently and within a team.

Minimum Qualifications

• PhD in data science, biomedical informatics, computational biology, neuroscience, or related field.
• Demonstrated experience in analyzing real-world medical data and applying machine learning techniques.

Preferred Qualifications

This position is part of a high-impact, data-driven research initiative focused on developing Precision Menopausal Hormone Therapy (P-MHT) strategies to reduce AD risk in women. The selected candidate will work at the forefront of translational neuroscience and women's health, leveraging multi-modal data-including genomics, EHR, and real-world clinical data-to build predictive models and inform therapeutic development. The role offers opportunities for collaboration with interdisciplinary teams in neuroscience, endocrinology, bioinformatics, and AI/ML. Demonstrated ability to independently prepare technical reports, visualizations, and manuscripts is preferred. Prior experience in neurodegenerative disease research, women's health, or pharmacogenomics. advantageous.

FLSA: Exempt

Full Time/Part Time: Full Time

Number of Hours Worked per Week: 40

Job FTE: 1.0

Work Calendar: Fiscal

Job Category: Research

Benefits Eligible: Yes - Full Benefits

Rate of Pay: NIH salary guidelines, Depends on Experience

Compensation Type: salary at 1.0 full-time equivalency (FTE)

Type of criminal background check required: Name-based criminal background check (non-security sensitive)

Number of Vacancies: 1

Contact Information for Candidates

Gloria Bloomer, gbloomer@arizona.edu

Documents Needed to Apply: Curriculum Vitae (CV) and Cover Letter

Special Instructions to Applicant

If invited to interview, please be prepared to provide three (3) professional references.