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Biological Data Science Internship Jobs in Utah (NOW HIRING)

Computational Biologist - AI Reviewer

Provo, UT ยท On-site +1

$90 - $120/hr

Scope of Work * Analyze and annotate complex biological data sets, focusing on applications ... Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

Cheminformatics Specialist - Remote

Provo, UT ยท On-site +1

$90 - $120/hr

Provide feedback and domain-specific insights to improve AI models in computational biology contexts. * Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science. * Experience collaborating in multidisciplinary or remote project environments is ...

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Biological Data Science Internship information

What are the key skills and qualifications needed to thrive as a biological data science intern, and why are they important?

To thrive as a Biological Data Science Intern, you need a solid background in biology, statistics, and programming, often supported by coursework or a degree in bioinformatics or a related field. Familiarity with tools like Python, R, and data analysis platforms, as well as experience with genomic databases and visualization software, is typically expected. Strong problem-solving, attention to detail, and teamwork skills help interns excel in collaborative research environments. These abilities enable accurate analysis of complex biological data and contribute to meaningful scientific discoveries.

What types of projects do interns typically work on during a biological data science internship?

Biological Data Science interns often work on projects involving the analysis of large biological datasets, such as genomic, proteomic, or clinical data. Typical tasks may include cleaning and preprocessing data, developing statistical models, and visualizing complex biological patterns. Interns frequently collaborate with both data scientists and biologists, gaining exposure to interdisciplinary teamwork and real-world research challenges. This hands-on experience helps interns build both their technical and scientific communication skills, making it a valuable stepping stone for careers in bioinformatics, computational biology, or related fields.

What is the difference between Biological Data Science Internship vs Biological Data Analyst?

AspectBiological Data Science InternshipBiological Data Analyst
Required CredentialsUndergraduate or graduate student in biology, data science, or related fieldBachelor's or master's in biology, data science, or related field; sometimes requires experience
Work EnvironmentResearch labs, biotech companies, academic institutions, often temporary or project-basedCorporate or research settings, ongoing role with regular hours
Employer & Industry UsageInternships offered by biotech firms, research institutions, universitiesFull-time roles in biotech, pharmaceuticals, research organizations

The Biological Data Science Internship is typically a temporary, entry-level position aimed at students gaining practical experience, whereas a Biological Data Analyst is a full-time role requiring more experience and responsibility. Internships focus on learning and skill development, while analysts handle ongoing data analysis tasks in professional settings.

What is a biological data science internship?

A Biological Data Science Internship is a temporary position for students or recent graduates to gain practical experience working at the intersection of biology and data science. Interns typically analyze biological datasets using computational tools, statistical methods, and programming languages such as Python or R. They may work on projects involving genomics, bioinformatics, drug discovery, or ecological modeling. The internship helps individuals develop both technical and domain-specific skills, preparing them for future careers in research, biotechnology, or academia.
What are popular job titles related to Biological Data Science Internship jobs in Utah? For Biological Data Science Internship jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Biological Data Science Internship jobs? Cities in Utah with the most Biological Data Science Internship job openings:

Computational Biologist - AI Reviewer

micro1 AI

Saint George, UT โ€ข On-site, Remote

$90 - $120/hr

Part-time

Posted 10 days ago


Job description

Role Title: Computational Biology Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology Experts to contribute their advanced scientific knowledge to a dynamic customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required โ€” your domain knowledge is what matters.


Scope of Work

  1. Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry.
  2. Provide feedback and domain-specific insights to improve AI models in computational biology contexts.
  3. Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with industry standards.
  4. Develop and review problem sets, case studies, or scenarios based on real-world medicinal chemistry challenges.
  5. Collaborate asynchronously with other experts to validate findings and share perspectives on project deliverables.
  6. Contribute to the refinement of data curation methodologies and best practices in computational biology.


Preferred Qualifications

  1. Advanced degree (PhD, PharmD, or MSc) in computational biology, medicinal chemistry, bioinformatics, or a closely related field.
  2. Demonstrated expertise in medicinal chemistry, including experience with drug discovery or design.
  3. Strong analytical skills with a deep understanding of biological datasets and scientific literature.
  4. Experience applying computational methods to solve problems in chemistry or biology.
  5. Proficiency with relevant bioinformatics tools, cheminformatics platforms, or data analysis software.
  6. Excellent written communication skills to clearly explain complex scientific concepts to diverse audiences.
  7. Previous participation in cross-disciplinary or AI-driven scientific projects is a plus.