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Intern Data Science Neuroscience Jobs in Arizona

University of Arizona

Scientific Analyst II

Tucson, AZ · On-site

Ability to collaborate effectively within interdisciplinary teams spanning data science, neuroscience, clinical research, and epidemiology. * Ability to manage multiple concurrent projects and meet ...

Stryker

$35/hr

As an intern, you won't just observe -- you'll contribute to meaningful projects, gain exposure to ... The data science intern will help drive proactive and predictive insights that inform strategic ...

Stryker

$35/hr

As an intern, you won't just observe -- you'll contribute to meaningful projects, gain exposure to ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

Stryker

$35/hr

As an intern, you won't just observe -- you'll contribute to meaningful projects, gain exposure to ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

Stryker

$35/hr

As an intern, you won't just observe -- you'll contribute to meaningful projects, gain exposure to ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

Stryker

$35/hr

As an intern, you won't just observe -- you'll contribute to meaningful projects, gain exposure to ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

Stryker

$35/hr

As an intern, you won't just observe -- you'll contribute to meaningful projects, gain exposure to ... The data science intern will help drive proactive and predictive insights that inform strategic ...

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All JobsIntern Data Science Neuroscience JobsIntern Data Science Neuroscience Jobs in Arizona

Intern Data Science Neuroscience information

What is the difference between Intern Data Science Neuroscience vs Intern Data Analyst?

AspectIntern Data Science NeuroscienceIntern Data Analyst
Required CredentialsRelevant coursework in neuroscience, data science, programming skills (Python, R)Statistics, data analysis, basic programming knowledge
Work EnvironmentResearch labs, healthcare, biotech companiesBusiness, finance, marketing departments
Employer & Industry UsageUniversities, research institutions, biotech firmsCorporations, consulting firms, market research
Common Search & Comparison IntentUnderstanding roles in neuroscience-focused data scienceExploring data analysis internships in various industries

Intern Data Science Neuroscience typically involves applying data science techniques to neuroscience research, often in academic or biotech settings, requiring knowledge of neuroscience and programming. Intern Data Analyst roles focus on analyzing data for business insights across industries, emphasizing statistical skills. While both roles involve data analysis, the focus and industry environment differ significantly.

Can I become a data scientist with a neuroscience degree?

A neuroscience degree can provide a strong foundation for a data scientist role, especially if complemented with skills in programming, statistics, and data analysis tools like Python or R. Many data scientists have diverse academic backgrounds, and additional training or certifications in data science can enhance employability in this field.

What are the most commonly searched types of Data Science Neuroscience jobs in Arizona?

The most popular types of Data Science Neuroscience jobs in Arizona are:

What are popular job titles related to Intern Data Science Neuroscience jobs in Arizona?

For Intern Data Science Neuroscience jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Intern Data Science Neuroscience jobs in Arizona look for?

The top searched job categories for Intern Data Science Neuroscience jobs in Arizona are:

What cities in Arizona are hiring for Intern Data Science Neuroscience jobs?

Cities in Arizona with the most Intern Data Science Neuroscience job openings:

Intern Data Science Neuroscience jobs near you
Infographic showing various Intern Data Science Neuroscience job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Scientific Analyst II

Tucson, AZ • On-site

University of Arizona
Colleges, Universities, and Professional Schools • 10K+ employees
Learn more about University of Arizonaexternal

Full-time

Re-posted 24 days ago

University Of Arizona rating

7.4

Company rating: 7.4 out of 10

Based on 69 frontline employees who took The Breakroom Quiz

Job description

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 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.
  • Assist 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, Skills and Abilities:

  • Strong theoretical and applied knowledge of machine learning, deep learning, and statistical modeling.
  • Strong data wrangling and preprocessing skills for large, heterogeneous datasets.
  • Expert-level programming skills in Python and/or R; proficiency with ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost).
  • Knowledge of drug repurposing methodologies or network pharmacology.
  • Knowledge and familiarity with electronic medical records data analysis.
  • Knowledge and proficiency with SQL and database management.
  • Ability to collaborate effectively within interdisciplinary teams spanning data science, neuroscience, clinical research, and epidemiology.
  • Ability to manage multiple concurrent projects and meet deadlines.
  • Ability to critically evaluate scientific literature and translate findings into research hypotheses and analytical strategies.
  • Ability to communicate complex analytical results clearly to both technical and non-technical audiences.

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