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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

19Open Positions

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  • Algorithm Development Intern – Battery Insights

    Analog Devices
    Limerick, Ireland
    Found 1 month ago
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    Isar Aerospace
    Kiruna, Sweden
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  • Schülerpraktikum (all genders)

    MTU Aero Engines AG
    Langenhagen, Germany
    Found 3 months ago
  • Schülerpraktikum

    MTU Aero Engines AG
    Langenhagen, Germany
    Found 3 months ago
  • Schülerpraktikum (all genders)

    MTU Aero Engines AG
    Langenhagen, Germany
    Found 3 months ago

Algorithm Development Intern – Battery Insights

Analog Devices
Found 1 month ago
Location
Limerick, Ireland
Duration (Months)
6 Months
Time
Not disclosed
Work Mode
Not disclosed
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
1 month ago

Education

  • Master
  • PhD

Skills & Qualifications

Technical Skills

  • data science
  • applied mathematics
  • statistics
  • signal processing
  • machine learning
  • Python
  • NumPy
  • pandas
  • scikit-learn
  • PyTorch
  • TensorFlow
  • data pipelines
  • model validation
  • experiment design
  • version control
  • Git
  • Jupyter
  • time-series analysis
  • unsupervised learning
  • predictive maintenance
  • battery systems
  • energy storage technologies
  • MLOps workflows
  • data versioning
  • model performance tracking

Soft Skills

  • problem-solving ability
  • clear communication of technical results
  • present quantitative results to both technical and non-technical audiences

Job Description

As an Algorithm Development Intern in the Battery Insights team, you will contribute to the design, prototyping, and evaluation of advanced algorithms that extract actionable information from battery data. You’ll work at the intersection of machine learning, signal processing, and embedded analytics, helping to translate raw sensing and operational data into insights about performance, health, and usage patterns. This role offers hands-on experience in applying data-driven methods to real-world energy storage systems, combining algorithmic innovation with strong engineering context. You will collaborate closely with experts in data science, systems engineering, and embedded software to support next-generation analytics for battery intelligence platforms.

Requirements

  • Currently pursuing a Master’s or Ph.D. in Electrical or Mechanical Engineering, Computer Science, Data Science, Applied Mathematics, or a related field.
  • Coursework or research experience in algorithm development, machine learning, or data analysis.
  • Proficiency in at least one programming language used for algorithm prototyping (Python, R, MATLAB, or C++).

Related Field

  • AI & Machine Learning

Related Subfield

  • Applied Machine Learning

Languages

  • English

Nice to Haves

  • time-series analysis
  • unsupervised learning
  • predictive maintenance use cases
  • battery systems
  • energy storage technologies
  • MLOps workflows
  • data versioning
  • model performance tracking
  • presenting quantitative results to both technical and non-technical audiences
▶Apply Now

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