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Bioinformatics Machine Learning Internship Jobs in Texas

Avride

Machine Learning Engineer Internship

Austin, TX · On-site

About the Internship At Avride, ML Engineer Interns operate at the intersection of cutting-edge ... Machine Learning / Math Foundation: Strong understanding of deep learning, reinforcement learning ...

Avride

Machine Learning Engineer Internship

Austin, TX · On-site

About the Internship At Avride, ML Engineer Interns operate at the intersection of cutting-edge ... Machine Learning / Math Foundation: Strong understanding of deep learning, reinforcement learning ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98K - $129K/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 ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98K - $130K/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 ...

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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 Texas? The most popular types of Bioinformatics Machine Learning jobs in Texas are:
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Bioinformatics Machine Learning Internship jobs near you
Sr. Bioinformatics ML/AI Engineer

Sr. Bioinformatics ML/AI Engineer

Baylor Miraca Genetics Laboratories, LLC

Houston, TX

Full-time

Posted 3 days ago

Job description

A seasoned machine learning and AI application engineer with strong knowledge and hands-on experience in bioinformatics, genomic/clinical data modeling, AI/GenAI application development, data engineering, and cloud computing.

QUALIFICATIONS:

  • Education:
    • Master's or higher degree in Computer Engineering, Data Science, Bioinformatics, Machine Learning, and Data modeling, or related field with five (5) years of experience in genomic data analysis and application development.
  • Experience:
    • Hands-on experience in clinical bioinformatics pipeline development, including secondary/tertiary analysis, variant interpretation and classification pipeline R&D, and automated report generation
    • Hands-on experience in human genetics/multi-omics data modeling and application development, especially in next-generation sequencing data
    • Hands-on experience in machine learning framework (such as Huggingface, TensorFlow)
    • Hands-on experience in automated and scalable AI/GenAI application evaluation, development, and deployment.
    • Hands-on experience in RAG AI framework
    • Hands-on experience with scripting languages, such as Bash and Python
    • Strong experience in cloud platform (Azure) and data services (data lakehouse/data warehouse)
    • Experience in context-aware OCR
    • Experience in databases, including SQL and NoSQL
    • Familiarity with advanced data visualization techniques
    • DevOps experience such as unit testing, CI/CD is a plus.
    • Strong curiosity and the ability to learn quickly and adapt to a fast-changing environment

DUTIES AND RESPONSIBILITIES:

  • Serves as the SME in Bioinformatics ML/AI application development in a clinical genetic testing setting. Provides hands-on support towards building the company’s next-generation bioinformatics ML/AI platform
  • Designs, develops, evaluates, and deploys state-of-the-art ML/AI solutions to gain valuable data insights based on the genetical, phenotypical, and clinical datasets
  • Evaluates, adopts, and customizes GenAI models based on both internal and external datasets to enhance the overall performance of the genetic testing workflow
  • Supports both internal and external data requirements by leveraging AI/ML and GenAI capabilities to keep up with the increasing demands of the business
  • Collaborates in a multidisciplinary and regulated clinical diagnostics environment with geneticists, bioinformaticians, software engineers, and IT infrastructure professionals

PHYSICAL DEMANDS AND WORK ENVIRONMENT:

  • Frequently required to sit
  • Frequently required to stand
  • Frequently required to utilize hand and finger dexterity
  • Frequently required to talk or hear
  • Frequently required to utilize visual acuity to operate equipment, read technical information, and/or use a keyboard
  • Occasionally exposed to bloodborne and airborne pathogens or infectious materials

EEO Statement:

Baylor Genetics is proud to be an equal opportunity employer dedicated to building an inclusive and diverse workforce. We do not discriminate based on race, religion, color, national origin, sex, sexual orientation, age, gender identity, veteran status, disability, genetic information, pregnancy, childbirth, or related medical conditions, or any other status protected under applicable federal, state, or local law.

Summary:

The Director, Corporate Financial Planning & Analysis is responsible for leading Baylor Genetics’ strategic financial planning, budgeting, forecasting, FP&A process improvement. This role plays a critical part in aligning financial strategy with long-term business goals. The Director will provide executive-level insights to leadership and external stakeholders while ensuring financial models and projections reflect the organization’s growth trajectory and performance.

Qualifications and Experience:
  • Education:
    • Bachelor's degree in Finance, Accounting, or a related field; MBA or relevant advanced degree preferred.
Experience:
  • Minimum of 10 years of experience in financial planning and analysis or corporate finance
  • At least 3 years in a financial leadership role
  • Proven success in FP&A process improvement, experience in Adaptive planning platform implementation required
  • Strong background in financial modeling, budgeting, and strategic forecasting
Duties and Responsibilities:
  • Strategic Financial Planning & Forecasting:
    • Lead the development of company-wide financial models and long-term forecasts
    • Translate strategic objectives into detailed financial plans aligned with organizational priorities
    • Collaborate with executive leadership to assess financial performance, risks, and growth opportunities
Budget and Forecast Management:
  • Oversee the annual budgeting process and rolling forecasts
  • Ensure alignment between actual results and forecasts, identifying key trends and drivers
  • Partner with department heads to develop financially sound operational plans
Revenue Analysis & Decision Support:
  • Lead revenue and margin analysis to support strategic decision-making
  • Drive business performance by analyzing sales trends, pricing strategies, and market dynamics
  • Provide financial insights that support resource allocation and investment decisions
Dashboards, Planning and Reporting:
  • Develop and maintain dashboards, planning and reporting tools for executive and departmental use including Adaptive planning platform
  • Provide timely and actionable financial insights to guide company performance
Team Leadership:
  • Build and lead a high-performing FP&A team
  • Foster a culture of collaboration, continuous improvement, and accountability
Physical Demands and Work Environment:
  • Frequently required to
  • Frequently required to utilize hand and finger
  • Frequently required to talk or
EEO Statement:

Baylor Genetics is proud to be an equal opportunity employer dedicated to building an inclusive and diverse workforce. We do not discriminate based on race, religion, color, national origin, sex, sexual orientation, age, gender identity, veteran status, disability, genetic information, pregnancy, childbirth, or related medical conditions, or any other status protected under applicable federal, state, or local law.

Note to Recruiters:

We value building direct relationships with our candidates and prefer to manage our hiring process internally. While we occasionally partner with select recruitment agencies for specialized roles, we do not accept unsolicited resumes from recruiters or agencies without a written agreement executed by the authorized signatory for Baylor Genetics ("Agreement"). Any resumes submitted to Baylor Genetics in the absence of an Agreement executed by Baylor Genetics' authorized signatory will be considered the property of Baylor Genetics, and Baylor Genetics will not be obligated to pay any associated recruitment fees.