Scientific Analyst II

Duties & Responsibilities

• Data Analysis and Machine Learning Pipeline Development
• Apply supervised and unsupervised machine learning algorithms 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.
• Drug Repurposing Research And Bioinformatics Analysis
• Collaborate 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.
• 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 manuscripts, conference presentations, and grant applications reporting research findings on MHT, menopause, and neurodegenerative disease.
• Present results to interdisciplinary research teams, departmental seminars, and external stakeholders.
• Collaborate closely with Dr. Francesca Vitali, co-investigators, and consortium partners.
• Maintain thorough documentation of analytical methods to ensure transparency and reproducibility.
• Participate in lab meetings, journal clubs, and professional development activities.

Research Infrastructure And Continuous Improvement

• Maintain and improve lab computational infrastructure, including code repositories (GitHub), analytical workflows, and documentation standards.
• Evaluate and adopt emerging AI/ML tools and methodologies relevant to brain science research.
• Aid in training junior lab members or graduate students on data science methods and tools as needed.
• Stay current with literature in neurodegenerative disease, computational knowledge.