Scientific Analyst II

Scientific Analyst II

Posting Number
req
25756

Department
UAHS Brain Science

Department Website Link
(Use the "Apply for this Job" box below)./

Location
Tucson Campus

Address
Tucson, AZ USA

Position Highlights

The Center for Innovation in Brain Science (CIBS) at the University of Arizona is seeking a Scientific Analyst II to support data science research focused on neurodegenerative diseases, including Alzheimer's Disease (AD), Parkinson's Disease (PD), Multiple Sclerosis (MS), and Amyotrophic Lateral Sclerosis (ALS). The analyst will work with large-scale biomedical datasets, including UK Biobank, All of Us, Insight, and electronic medical records, to investigate the role of menopausal hormone therapy (MHT) and menopause on brain health, and to identify and evaluate drug repurposing candidates for neurodegenerative disease prevention and treatment.

The position requires advanced expertise in data science, artificial intelligence, and machine learning to develop, apply, and interpret analytical pipelines that integrate multi-modal clinical, genomic, and epidemiological data. This role directly contributes to the lab's mission of translating large-scale data insights into actionable strategies for the prevention and treatment of neurodegenerative conditions. The primary deliverables of this role are computational pipelines, ML models, and exploratory data outputs.

The Center for Innovation in Brain Science is an "all brains on deck" research environment designed for highly-integrated, collaborative research through innovative team science. With expertise spanning discovery, translational and clinical science, we are addressing complex issues across four age-associated neurodegenerative diseases. Bringing expertise in Alzheimer's, Parkinson's, Multiple Sclerosis and ALS, aging, bioenergetics of the brain, immunology, stem cell biology, big data computational science, animal models of neurodegenerative disease, drug design and synthesis, FDA regulatory and toxicology requirements and clinical trial design and conduct.

This position is funded through research grants. Continuation of the position is contingent upon availability of funding. The successful candidate will join a dynamic, interdisciplinary team at the Center for Innovation in Brain Science (CIBS), working at the forefront of computational neuroscience and population health research. The analyst will have opportunities to contribute to high-impact publications, grant applications, and collaborative multi-site research projects.
This position offers a hybrid work arrangement, combining on-site work at the University of Arizona campus with remote work flexibility.
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!

The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please .

Duties & Responsibilities

Data Analysis and Machine Learning Pipeline Development:

• Under moderate guidance collaborate in the design, develop, and execution of machine learning and AI-driven analytical pipelines to analyze large-scale biomedical datasets from UK Biobank, All of Us, Insight, and electronic medical records.
• Apply supervised and unsupervised machine learning algorithms (e.g., logistic regression, random forests, deep learning) to identify risk factors, biomarkers, and patterns associated with neurodegenerative diseases and the effects of menopausal hormone therapy (MHT) on brain health.
• Collaborate on the development and validation of predictive models integrating genomic, clinical, lifestyle, and imaging data using general knowledge of principals, theories and concepts.

Drug Repurposing Research and Bioinformatics Analysis:

• Collaborating in computational drug repurposing analyses to identify existing FDA-approved compounds with potential efficacy for AD, PD, MS, and ALS prevention and treatment. Integrate multi-omics data (genomics, transcriptomics, proteomics) with clinical outcomes data to prioritize drug candidates.
• Collaborate with wet lab and clinical teams to support translational interpretation of findings.

Epidemiological and Clinical Data Management and Harmonization:

• Access, curate, harmonize, and manage large population-based datasets including UK Biobank, All of Us, and institutional EMR data.
• Ensure data quality, reproducibility, and compliance with data use agreements and IRB protocols.
• Collaborate in the develop and maintenance of reproducible data pipelines using Python, R, and high performance computer.
• Perform statistical analyses including survival analysis, longitudinal modeling, and causal inference.

Scientific Communication, Dissemination, and Collaboration:

• Compare and contribute to peer-reviewed…