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Bioinformatics Machine Learning Internship Jobs in Alabama

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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.

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Bioinformatics Machine Learning Internship jobs near you

Mid-level Software Developer: HSV-26123

Http://www.decibelresearch.com/

Huntsville, AL

Full-time

Re-posted 3 days ago

Job description

deciBel Research has an immediate opening for a Mid-level Software Developer in Huntsville, AL.

Position Description:

We are seeking a mid-level AI Software Developer (5–10 years of experience) who is passionate about applying artificial intelligence to transform complex engineering and business data into actionable insights. In this role, you'll develop intelligent analytics solutions that integrate data from engineering and enterprise tools such as Cameo Systems Modeler, Tableau, and other structured and unstructured data sources to create dynamic dashboards, visualizations, and decision-support capabilities.

You'll work closely with systems engineers, software developers, data engineers, and product stakeholders to build AI-enabled solutions that improve visibility into complex programs and accelerate decision-making. We value practical innovation, technical curiosity, and engineers who enjoy solving challenging problems while delivering software that has an immediate impact.

Responsibilities Include

  • Design, develop, and maintain AI-enabled applications using technologies such as Python, machine learning frameworks, APIs, and modern software engineering practices.
  • Develop intelligent data pipelines that ingest, correlate, and analyze information from tools including Cameo Systems Modeler, Tableau, databases, and other enterprise data sources.
  • Build AI-powered dashboards, visualizations, and interactive analytics that transform complex technical and program data into actionable insights for engineers and decision-makers.
  • Develop retrieval, summarization, and natural language query capabilities using modern AI and Large Language Model (LLM) technologies.
  • Create scalable data models and services that support analytics, reporting, and digital engineering initiatives.
  • Collaborate with systems engineers, software developers, data scientists, UX designers, and product owners in an agile, cross-functional environment.
  • Integrate AI capabilities with existing enterprise applications through REST APIs, cloud services, and modern software architectures.
  • Participate in technical design reviews, code reviews, architecture discussions, and continuous improvement activities.
  • Prototype innovative AI solutions and mature successful concepts into production-ready software.
  • Stay current with emerging AI, machine learning, and data visualization technologies, applying them thoughtfully to solve real-world engineering and business challenges.

Education Requirements:

BS Computer Science or Computer Engineering

Experience Requirements:

  • A degree in Computer Science or related field and some hands-on experience, personal projects, GitHub contributions, bootcamp experience, or internships.
  • Demonstrative experience with at least one modern programming language (Python, C++, Rust)
  • Experience with Linux operating system
  • Built at least one meaningful service/API
  • System-level thinking
  • Git + Linux proficiency
  • Curiosity, problem-solving, and a willingness to experiment.
  • Comfort working in collaborative, iterative development environments.
  • Strong communication skills and a desire to grow.

Special Skills Desired:

  • 5–10 years of software development experience with strong proficiency in Python or similar scripting languages.
  • Experience developing applications using Large Language Models (LLMs), generative AI frameworks, or machine learning technologies.
  • Experience integrating data from engineering, project management, or business intelligence platforms such as Cameo Systems Modeler, Tableau, databases, or similar enterprise tools.
  • Experience building dashboards and data visualization solutions using Tableau, Power BI, Plotly Dash, Streamlit, or similar technologies.
  • Familiarity with AI orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, or equivalent.
  • Experience developing RESTful APIs and working with structured and unstructured data.
  • Knowledge of vector databases, Retrieval-Augmented Generation (RAG), embeddings, or semantic search is highly desirable.
  • Experience with cloud platforms (AWS, Azure, or Google Cloud) and containerized applications is a plus.
  • Strong problem-solving, communication, and collaboration skills.

Applicant selected must have an active Secret security clearance. Must be a U.S. Citizen.

Apply