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Bioinformatics Machine Learning Internship Jobs in California

ROSALIND

Bioinformatics Engineer

San Diego, CA · On-site

... machine learning algorithms for implementation within the ROSALIND multi-tenant SaaS platform • Be flexible and passionate about bioinformatics alchemy to support greater discovery into biology ...

ChromoLogic

Senior Scientist, Bioinformatics

Monrovia, CA · On-site

$90K - $120K/yr

Apply advanced machine learning, Bayesian statistics, and predictive modeling techniques to identify biologically meaningful patterns and biomarkers * Design and execute end-to-end analytical ...

Apple

Machine Learning Engineer - Health AIML

Cupertino, CA

$216K - $324K/yr

  • Medical

  • Dental

  • Retirement

D. in Computer Science, Machine Learning, Bioinformatics, or a related field. Strong background in generative models, natural language processing (NLP), and large language models (LLMs). 5+ years of ...

ChromoLogic

Senior Scientist, Bioinformatics

Monrovia, CA · On-site

$90K - $120K/yr

Apply advanced machine learning, Bayesian statistics, and predictive modeling techniques to identify biologically meaningful patterns and biomarkers * Design and execute end-to-end analytical ...

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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 California?

The most popular types of Bioinformatics Machine Learning jobs in California are:

What are popular job titles related to Bioinformatics Machine Learning Internship jobs in California?

For Bioinformatics Machine Learning Internship jobs in California, the most frequently searched job titles are:

What job categories do people searching Bioinformatics Machine Learning Internship jobs in California look for?

The top searched job categories for Bioinformatics Machine Learning Internship jobs in California are:

What cities in California are hiring for Bioinformatics Machine Learning Internship jobs?

Cities in California 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 California as of August 2026, with employment types broken down into 7% Internship, 72% Full Time, 14% Part Time, and 7% Temporary. Highlights an 100% In-person job distribution.

Director, Machine Learning, Virtual Cell Initiative

Arc Institute

Palo Alto, CA • On-site

Full-time

Re-posted 19 days ago

Job description

Job Summary:
Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. The Director of Machine Learning will lead a team in developing advanced machine learning models for the Virtual Cell Initiative, focusing on single-cell genomic data to revolutionize drug discovery.
Responsibilities:
• Lead/build a team of 6 ML research scientists and engineers augmented with undergrad/masters/PhD students to contribute to the development of a state-of-the-art foundation model and agentic framework for understanding how cells respond to perturbations.
• Work in an active learning loop with Arc’s wet lab scientists to shape the world's largest and most diverse set of single cell training data across many cell contexts.
• Collaborate closely with other research groups to integrate genomics, functional track,and omics data more broadly beyond scRNA-seq data and Perturb-seq
• Stay up to date on the latest in frontier ML research and pioneer new architectures and approaches.
• The ultimate goal is to build a high utility virtual cell model for use by biologists worldwide. We publish our breakthroughs to widely accelerate scientific progress and partner with some of the biggest names in AI.
• Commit to a collaborative and inclusive team environment, sharing expertise and mentoring others.
• Attract the very best talent in the world to support VCI initiative goals
Qualifications:
Required:
• PhD in Computational Biology, Bioinformatics, Machine Learning, or a related field.
• Minimum of 5 years of experience working in/with machine learning, well versed in frameworks such as Pytorch, TensorFlow, JAX, etc.
• Proven experience leading research teams in a fast paced, multi-disciplinary environment.
• Experience with or strong interest in biology with ability to communicate and collaborate successfully with biologists and pure ML engineers.
• Excellent communication skills, both written and verbal, with a strong track record of presentations and publications.
Company:
Arc Institute is a biomedical science and research technology company. Founded in 2021, the company is headquartered in Palo Alto, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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