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Bioinformatics Machine Learning Internship Jobs in Boston, MA

Scientist, Bioinformatics Job Locations US-Remote | US-MO-St. Louis ID 2026-19291 Job Function ... Hands-on experience developing machine-learning or deep-learning models (training, evaluation, and ...

Summary: The Machine Learning Engineer (SMTS) designs and implements machine learning (ML ... bioinformatics, and more. Duties/Responsibilities Designs and develops AI models to meet project ...

Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

The Alexa AI team is looking for a passionate, talented, and inventive Machine Learning Engineer ... BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ ...

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Bioinformatics Machine Learning Internship information

See Boston, MA salary details

$27.7K

$46.3K

$95.6K

How much do bioinformatics machine learning internship jobs pay per year?

As of Jul 13, 2026, the average yearly pay for bioinformatics machine learning internship in Boston, MA is $46,263.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,300.00 and $50,000.00 per year, depending on experience, location, and employer.

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 Boston, MA? The most popular types of Bioinformatics Machine Learning jobs in Boston, MA are:
What are popular job titles related to Bioinformatics Machine Learning Internship jobs in Boston, MA? For Bioinformatics Machine Learning Internship jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Bioinformatics Machine Learning Internship jobs in Boston, MA look for? The top searched job categories for Bioinformatics Machine Learning Internship jobs in Boston, MA are:
Microbiome Computational Scientist

Microbiome Computational Scientist

Mass General Brigham

Boston, MA • On-site

Full-time

Posted 27 days ago


Brigham and Women's Hospital rating

8.1

Company rating: 8.1 out of 10

Based on 100 frontline employees who took The Breakroom Quiz

116th of 1,020 rated hospitals


Job description

Site: The Brigham and Women's Hospital, Inc.
Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.
Job Summary
PLEASE SUBMIT A COVER LETTER WITH YOUR APPLICATION.
The Microbiome AI/Deep Learning Lab in the Massachusetts Host-Microbiome Center and Division of Computational Pathology at Brigham and Women's Hospital/Harvard Medical School is seeking a computational scientist with experience in microbiome bioinformatics and machine learning. You will develop, deploy, and apply microbiome and bioinformatics machine learning approaches, with a special emphasis on deep learning, to a variety of microbiology data sources. Applications will include forecasting microbial population dynamics in the gut, characterizing the impact of spatial structure of the microbiome, predicting impact of the microbiome on host phenotype, tracking infections in human populations, elucidating microbial metabolism, and discovering functions of uncharacterized microbial metabolites and proteins.
Applicants should have a high level of interest in:
• A long-term career in an academic medical environment, with the potential for your work to have a direct impact on healthcare outcomes.
• Applying new deep learning technologies to biomedical problems.
• Advancing knowledge of the microbiome and its role in human health and disease.
• Working on an interdisciplinary team and collaborating with computational, wet lab and clinical scientists.
• Engaging with the broader research community to advance applications of AI/deep learning for the microbiome.
About the environment: The Microbiome AI/Deep Learning Lab is an initiative within the Massachusetts Host-Microbiome Center (MHMC) and the Division of Computational Pathology (DCP) at Brigham and Women's Hospital (BWH)/Harvard Medical School (HMS). With recent funding from the Massachusetts Life Sciences Center, the Lab has built a state-of-the-art compute cluster with extensive GPU and CPU nodes, with the objective of making advanced deep learning technologies broadly available to microbiome researchers. The MHMC is a research and core facility that has worked with 100+ groups in the US and internationally to promote understanding of host-microbiome interactions in health and disease, emphasizing a focus on function to define causative effects of the microbiota and to harness this knowledge in developing new therapies, diagnostics and further commercial applications. The DCP is a research division with a broad mandate to develop and apply advanced computational methods for furthering the understanding, diagnosis and treatment of human diseases. BWH is an HMS affiliated teaching hospital, adjacent to the HMS main quad, and the second largest non-university recipient of NIH research funding.
PRINCIPAL DUTIES AND RESPONSIBILITIES:
Engage in research developing and applying bioinformatic and machine learning approaches, for a variety of microbiology data sources, including next generation sequencing and metabolomic data.
Substantially contribute to scientific publications and grant applications.
Analyze datasets and produce visualizations and written reports about scientific findings.
Deploy computational pipelines on local workstations and on high performance CPU and GPU clusters.
Organize and curate large datasets using structured approaches, including database systems.
Engage with trainees and other users of the MHMC to facilitate use of computing resources and application of machine learning technologies for the microbiome.
Other duties as assigned.
Qualifications
QUALIFICATIONS:
  • PhD in Computational Biology, Computer Science, or related quantitative discipline.
  • Experience analyzing microbiome data and machine learning applications demonstrated through authorship on high-quality, peer-reviewed scientific publications.
  • 3+ years minimum Python programming experience.
  • 3+ years minimum experience working in high-performance computing environments.
  • Experience with microbiome bioinformatics methods and pipelines for next generation sequencing data analysis.
  • Experience with organizing and managing large multi-omics datasets.
  • Strong verbal and written communication, and interpersonal skills.
  • Experience with deep learning and PyTorch is highly desired

SKILLS/ABILITIES/COMPETENCIES REQUIRED:
  • Must be capable of contributing within an interdisciplinary team, exhibit a high level of initiative, and have an eagerness to learn new technologies.
  • Ability to manage entire projects in a research environment, from design to implementation, and interpretation of final results.
  • Must have experience analyzing microbiome data.
  • Must possess advanced knowledge of machine learning, including model development, training, testing and deploying.
  • Demonstrated ability to develop and implement computational approaches for analyzing complex biomedical datasets including next generation sequencing data.
  • Demonstrated ability to manage large and complex biomedical datasets, using tools such as databases.
  • Excellent written and verbal communication skills with demonstrated ability to communicate complex results to both technical and non-technical audiences, through publications and presentations.
  • Ability to implement machine learning methods in Python; experience with deep learning and using PyTorch is highly desired.
  • Knowledge of software engineering best practices, including source code management/control (e.g., Git) and containerization approaches.
  • Experience with high-performance computing environments, including scheduling systems, e.g., SLURM.
  • Ability to multitask and prioritize work, to achieve desired goals and deliverables.
  • Ability to share expertise, coach, and give general direction to others of different skill sets, backgrounds and levels.

Additional Job Details (if applicable)
Remote Type
Onsite
Work Location
60 Fenwood Road
Scheduled Weekly Hours
40
Employee Type
Regular
Work Shift
Day (United States of America)
Pay Range
$93,953.60 - $136,739.20/Annual
Grade
7
At Mass General Brigham, we believe in recognizing and rewarding the unique value each team member brings to our organization. Our approach to determining base pay is comprehensive, and any offer extended will take into account your skills, relevant experience if applicable, education, certifications and other essential factors. The base pay information provided offers an estimate based on the minimum job qualifications; however, it does not encompass all elements contributing to your total compensation package. In addition to competitive base pay, we offer comprehensive benefits, career advancement opportunities, differentials, premiums and bonuses as applicable and recognition programs designed to celebrate your contributions and support your professional growth. We invite you to apply, and our Talent Acquisition team will provide an overview of your potential compensation and benefits package.
EEO Statement:
2200 The Brigham and Women's Hospital, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veteran's Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at (857)-282-7642.
Mass General Brigham Competency Framework
At Mass General Brigham, our competency framework defines what effective leadership "looks like" by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.

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