ZipRecruiter

Log In

1

Contract Biomedical Machine Learning Jobs in Arizona

University of Arizona

Scientific Analyst II

Tucson, AZ · On-site

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 ...

Staffingine LLC

AIML Engineer

Scottsdale, AZ · On-site

Contract to Hire * Design and implement scalable MLOps supportive data pipelines for data ingestion ... Experience implementing and supporting endtoend Machine Learning workflows and patterns * Expert ...

Lifekind Health

Data Scientist

Scottsdale, AZ · On-site

$80K - $120K/yr

Machine Learning & Predictive Analytics: * Develop and deploy AI/ML models that power key products ... Master's degree in Data Science, CS, Statistics, Biomedical Informatics, or related field preferred ...

Staffingine LLC

AI Engineer

Phoenix, AZ · On-site

Contract * Develop and implement AI solutions using Python and AI frameworks such as Langgraph and ... Design develop and deploy AI and machine learning models using Python and relevant AI stacks Manage ...

Staffingine LLC

AI ML Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Contract * Programming Languages Python Pandas NumPy Scikitlearn SQL * Statistical Modeling Machine Learning Regression Classification Clustering Time Series Forecasting * Data Visualization Power BI ...

previous pagenext page

Showing results 21-40

All JobsContract Biomedical Machine Learning JobsContract Biomedical Machine Learning Jobs in Arizona

Contract Biomedical Machine Learning information

What is the difference between Contract Biomedical Machine Learning vs Contract Data Scientist?

AspectContract Biomedical Machine LearningContract Data Scientist
CredentialsBackground in biomedical engineering, machine learning, data analysisBackground in statistics, computer science, data analysis
Work EnvironmentHealthcare, biotech, research labsTech companies, finance, consulting firms
Industry UsageMedical device development, clinical researchBusiness analytics, product development

Contract Biomedical Machine Learning specialists focus on applying machine learning techniques to biomedical data within healthcare and biotech settings. In contrast, Contract Data Scientists work across various industries analyzing data to inform business decisions. While both roles require data analysis skills, Contract Biomedical Machine Learning emphasizes biomedical knowledge and healthcare applications.

What are popular job titles related to Contract Biomedical Machine Learning jobs in Arizona?

For Contract Biomedical Machine Learning jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Contract Biomedical Machine Learning jobs in Arizona look for?

The top searched job categories for Contract Biomedical Machine Learning jobs in Arizona are:

What cities in Arizona are hiring for Contract Biomedical Machine Learning jobs?

Cities in Arizona with the most Contract Biomedical Machine Learning job openings:

Contract Biomedical Machine Learning jobs near you

Scientific Analyst II

University of Arizona

Tucson, AZ • On-site

Full-time

Re-posted 2 days ago

University Of Arizona rating

7.3

Company rating: 7.3 out of 10

Based on 68 frontline employees who took The Breakroom Quiz

363rd of 620 rated colleges and universities

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.

What University Of Arizona employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply