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Biology Machine Learning Intern Jobs in Colorado

$50/hr

Responsibilities As a research intern, you will investigate and apply novel algorithms related to ... Strong analytical and programming skills in deep learning using frameworks and tools for machine ...

$50/hr

Responsibilities As a research intern, you will investigate and apply novel algorithms related to ... Strong analytical and programming skills in deep learning using frameworks and tools for machine ...

$50/hr

Responsibilities As a research intern, you will investigate and apply novel algorithms related to ... Strong analytical and programming skills in deep learning using frameworks and tools for machine ...

Showing results 41-60

Biology Machine Learning Intern information

What does a biology machine learning intern do?

A Biology Machine Learning Intern works at the intersection of biology and computer science, applying machine learning techniques to analyze biological data. Their tasks often include processing large datasets, building predictive models, and supporting research projects that use artificial intelligence to solve biological problems. Interns may work on projects like drug discovery, genomics, or protein structure prediction, and typically collaborate with scientists and engineers. This role helps bridge the gap between experimental biology and data-driven insights.

What kinds of projects does a biology machine learning intern typically work on, and how do these projects contribute to the team?

Biology Machine Learning Interns often work on interdisciplinary projects that apply machine learning techniques to analyze biological data, such as genomics, protein structures, or cellular imaging. These projects may involve developing predictive models, automating data processing pipelines, or extracting meaningful patterns from large, complex datasets. Interns usually collaborate closely with both biologists and data scientists, gaining hands-on experience and contributing valuable insights that support ongoing research or product development. This collaborative environment not only enhances technical skills but also provides exposure to real-world applications of AI in life sciences.

What are the key skills and qualifications needed to thrive as a biology machine learning intern, and why are they important?

To thrive as a Biology Machine Learning Intern, you need a foundational understanding of biology, statistics, and programming (usually Python or R), often supported by coursework or a degree in a related field. Familiarity with machine learning frameworks (such as TensorFlow or scikit-learn), bioinformatics tools, and data analysis platforms is typically expected. Strong problem-solving abilities, attention to detail, and teamwork skills help interns excel in interdisciplinary research environments. These skills and qualities are crucial for effectively analyzing biological data, developing models, and contributing to innovative scientific solutions.

What are popular job titles related to Biology Machine Learning Intern jobs in Colorado?

For Biology Machine Learning Intern jobs in Colorado, the most frequently searched job titles are:

What cities in Colorado are hiring for Biology Machine Learning Intern jobs?

Cities in Colorado with the most Biology Machine Learning Intern job openings:

Infographic showing various Biology Machine Learning Intern job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Scientist I, Computation Protein Design

Alta Resource Technologies, Inc.

Boulder, CO โ€ข On-site

$140K - $175K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 12 days ago


Job description

About the Role:

We are seeking a highly skilled Scientist I, Computation Protein Design to join our team and drive innovation in protein design and engineering through good data practices, robust analytical methods and machine learning. This role focuses on leveraging and optimizing foundational AI models to accelerate our protein engineering pipeline. The ideal candidate will have deep expertise in model fine-tuning, evaluation, and selection, with strong data engineering capabilities to support cutting-edge computational biology research.

Key Responsibilities:

Model Development

  • Fine-tune, adapt, and use foundational protein models (e.g., BoltzGen, ESM, OpenFold derivatives) for protein engineering applicationsย ย ย ย ย 
  • Develop and implement rigorous evaluation frameworks to assess model performance, including metrics for protein structure prediction, sequence optimization, and functional property prediction
  • Conduct comprehensive benchmarking studies to identify and recommend the most suitable foundational models for various protein engineering tasks
  • Design and execute computational experiments to validate model predictions against experimental data
  • Leverage multiple information sources (including bioinformatic, structural, simulations, and experimental performance data) to improve internal models and develop agentic frameworks

Cross-functional collaboration

  • Collaborate with the Applied Biology team to translate models into actionable insights.ย ย 
  • Create technical documentation including model assumptions, equations, validation results, and recommendations.
  • Provide technical mentorship and review for junior engineers and scientists.ย 
  • Clearly communicate technical findings, risks and recommendations to leadership and project stakeholders.ย 

Data Management, Analysis and Integration

  • Contribute to developing data management systems that meet FAIR principles.ย 
  • Develop analysis code to support the team in analyzing experimental data.
  • Engineer data into vectorized format for MCP integration
  • Utilize experimental data to validate and improve model development.ย 

Required Qualifications:

  • Ph.D. in Computational Biology, Bioinformatics, Computer Science with 1-3 years of relevant industry or post-doctoral experience, or M.S. with 6+ years of relevant industry experience
  • Hands-on experience with protein foundation models such as ESM-2, ESM-3, ProteinMPNN, RFdiffusion, AlphaFold, or similar architectures
  • Knowledge of protein design software and molecular modeling tools (Rosetta, PyMOL, Chimera)
  • Demonstrated experience fine-tuning and working with large-scale machine learning models, preferably protein or biological sequence models
  • Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, JAX)
  • Experience with model evaluation methodologies, including cross-validation, performance metrics, and statistical analysis
  • Solid understanding of protein structure, function, and the principles of protein engineering
  • Experience with high-performance computing environments and GPU-accelerated computing
  • Strong communication skills and ability to work collaboratively in interdisciplinary teams
  • US Citizenship required.

Preferred, But Not Required:

  • Experience with workflow management tools (Nextflow, Snakemake, or similar)
  • Familiarity with cloud computing platforms (AWS, GCP, Azure) and containerization (Docker, Singularity)
  • Experience with distributed computing frameworks (Dask, Ray, Spark)
  • Track record of publications or contributions to open-source projects in computational biology or machine learning

What We Offer:

  • The opportunity to lead a breakthrough program redefining U.S. supply chain resilience in critical materials.
  • A mission-driven, high-trust team operating at the intersection of innovation, national security, and sustainability.
  • High Impact & Visibility: Direct interaction and reporting to executive leadership.
  • Competitive compensation and benefits package.ย 
    • The starting pay range for this position is $140,000 to $175,000 commensurate with educational background and work experience.ย 
    • Benefits including, 401(K) medical, dental, and vision plans, or equivalent, will be provided.
    • Paid parental leave, paid sick leave, flexible time off, company holidays.ย