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Bioinformatics Machine Learning Internship Jobs in Utah

Utah State University

Postdoctoral Fellow I

Logan, UT · On-site

$42K - $57K/yr

Develop systems bioinformatics approaches including Machine Learning-based to decipher host-pathogen interaction networks in diverse Avian and HPAI strains. * Focus on system and data integration ...

Utah State University

Postdoctoral Fellow I

Logan, UT · On-site

$42K - $57K/yr

Develop systems bioinformatics approaches including Machine Learning-based to decipher host-pathogen interaction networks in diverse Avian and HPAI strains. * Focus on system and data integration ...

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Bioinformatics Machine Learning Internship information

What is a Bioinformatics Machine Learning Internship?

A Bioinformatics Machine Learning Internship is a temporary position, usually for students or recent graduates, where interns gain hands-on experience applying machine learning techniques to biological data. Interns may work on projects like analyzing genomic sequences, predicting protein structure, or developing algorithms for biomedical research. The role involves coding, data analysis, and collaborating with scientists to solve real-world biological problems. It offers exposure to both computational methods and biological sciences, preparing interns for careers in bioinformatics, data science, or research.

What are the key skills and qualifications needed to thrive as a Bioinformatics Machine Learning Intern, and why are they important?

To thrive as a Bioinformatics Machine Learning Intern, you need a solid background in biology, statistics, and computer science, typically supported by relevant coursework or a degree in bioinformatics, computational biology, or a related field. Familiarity with programming languages like Python or R, experience using bioinformatics tools (e.g., BLAST, Bioconductor), and knowledge of machine learning frameworks such as TensorFlow or scikit-learn are highly valued. Attention to detail, problem-solving skills, and effective communication help interns collaborate on interdisciplinary teams and interpret complex datasets. These skills ensure interns can contribute meaningfully to research projects, derive insights from biological data, and communicate findings clearly.

What are some typical projects or tasks a Bioinformatics Machine Learning Intern might work on during their internship?

As a Bioinformatics Machine Learning Intern, you'll often contribute to projects that involve developing and testing algorithms for analyzing biological data, such as genomic sequences or protein structures. Typical tasks may include preprocessing large datasets, implementing machine learning models to identify patterns or make predictions, and visualizing results for team discussions. Interns frequently collaborate with both computational scientists and experimental biologists, gaining exposure to interdisciplinary teamwork and real-world applications. This hands-on experience helps interns build both technical and domain-specific skills, preparing them for advanced roles in bioinformatics or data science.

What is the difference between Bioinformatics Machine Learning Internship vs Bioinformatics Data Analyst Internship?

AspectBioinformatics Machine Learning InternshipBioinformatics Data Analyst Internship
Required SkillsProgramming, machine learning, bioinformatics toolsData analysis, statistical skills, bioinformatics tools
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch labs, healthcare, biotech firms
Industry UsageDeveloping algorithms, predictive models in bioinformaticsAnalyzing biological data, generating reports

While both internships involve bioinformatics, the Bioinformatics Machine Learning Internship focuses on developing machine learning models and algorithms, whereas the Bioinformatics Data Analyst Internship emphasizes analyzing biological data and generating insights. Both roles require programming and bioinformatics skills but differ in their core focus and application.

What are the most commonly searched types of Bioinformatics Machine Learning jobs in Utah? The most popular types of Bioinformatics Machine Learning jobs in Utah are:
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What cities in Utah are hiring for Bioinformatics Machine Learning Internship jobs? Cities in Utah with the most Bioinformatics Machine Learning Internship job openings:
Bioinformatics Machine Learning Internship jobs near you
Infographic showing various Bioinformatics Machine Learning Internship job openings in Utah as of June 2026, with employment types broken down into 24% Internship, 52% Full Time, and 24% Part Time. Highlights an 88% In-person, 6% Hybrid, and 6% Remote job distribution.
Bioinformatics Analyst - UT

Bioinformatics Analyst - UT

GATC Health

Salt Lake City, UT • On-site

Full-time

Posted 3 days ago

Job description

Company Overview: GATC Health is an innovative TechBio company at the forefront of revolutionizing pharmaceutical discovery and accelerating their development through the integration of artificial intelligence (AI), science and finance. Our company is dedicated to advancing therapeutic discoveries and improving human health by leveraging the power of technology and interdisciplinary collaboration.
 
Position Overview: We are seeking a talented Bioinformatics Analyst to join our dynamic, multi-disciplinary team that is responsible for implementing and aiding in design and analysis software and informatics pipelines for primary, secondary, and tertiary analysis of data generated from transcriptional, proteomic, and mult-omic assays. As a Bioinformatics Scientist, you will innovate, develop and implement novel analysis methods for different data types from sparse to large and complex datasets to support the internal development and validation of new pharmaceutical assets and the development of end-user, customer-facing data analysis and visualization for biotech customers and stakeholders. A highly motivated scientist with broad expertise and experience in bioinformatics, computational biology, transcriptomics, proteomics and multi-omics would be an ideal fit for this position.
 
Roles and Responsibilities
  • Prep and Process data through GATC platform based on customer or internal end user requirements.
  • Implement primary and secondary analysis tools for GATC’s assays.
  • Work with cross-disciplinary R&D teams to develop and implement new discovery and risk assessment product applications.
  • Aid in Development and implementation processes and algorithms for multi-modal datasets, scalable to very large numbers of samples.
  • Engage with external collaborators on the evaluation of beta version products and analysis of novel data.
Role Requirements
  • Degree in computational biology, bioinformatics, computer science or similar.
  • Experience analyzing complex multi-omic datasets, including human or single cell data.
  • Experience implementing, and evaluating novel bioinformatics algorithms and pipelines.
  • Experience in programming in scripting (Python or similar) and interpreted languages (R, etc).
  • Demonstrated ability to become proficient in new fields and work with interdisciplinary teams.
  • Excellent verbal/written communication and interpersonal skills with scientist and non-scientists.
Role Preferences
  • Experience using or interfacing with machine learning algorithms.
  • Experience analyzing and interpreting large-scale human or single cell datasets.
  • Experience with professional software development methods and tools in a team environment.
  • Experience in programming in scripting (Python), interpreted (R ) and compiled languages (C++ / Rust / Java).
  • Experience working with collaborators, including lab scientists on multi-omic method development.
  • Experience visualizing scientific datasets and results.
  • Experience using cloud computing environments.
  • Computational biology and bioinformatics innovation.
Why Join Us:
• Opportunity to work at the intersection of technology and science, driving innovation in pharmaceutical discovery.
• Collaborative and inclusive work culture that values diversity, creativity, and continuous learning.
• Competitive compensation package, including salary, benefits, and opportunities for professional development.
• Chance to make a meaningful impact on human health and contribute to groundbreaking research and development projects.
 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.