R&D Research Algorithm & Data Science Intern 2026

Boston ScientificArden Hills, MN
49d$42,120 - $71,552Onsite

About The Position

Our R&D engineers are tasked with designing and developing implant products for the Active Implantable Systems (AIS) group. This includes technologies that monitor, support diagnosis and treat irregular heart rhythms, heart failure, and sudden cardiac arrest. AIS provides devices and therapies for a patient's entire continuum of care, from diagnostic to treatment. This division strives to innovate and create a paradigm shift that can solve unmet clinical needs and change what is possible for patients. Hear from Megan about her intern experience At Boston Scientific, we value collaboration and synergy. This role follows an onsite work model, requiring employees to be in our local office at least four days per week. Corporate housing and relocation are available for those who are eligible. Boston Scientific will not offer sponsorship or take over sponsorship of an employment VISA for this position at this time

Requirements

  • Masters or Ph.D. student. Must have at least one semester of school left post-internship to qualify.
  • Working towards a degree in Biomedical Engineering (EE emphasis), Electrical Engineering, Data Science, Neuroscience, or Mathematics.
  • Must be able to start internship on May 18th or 26th, 2026 and work for 12 weeks
  • Must have reliable transportation to/from work.
  • Demonstrated ability to build and refine algorithms using statistical and analytical methods for data-driven innovation.

Nice To Haves

  • Proficient in Python, Kotlin, or Java, with hands-on experience using MATLAB for algorithm development, simulation, or signal processing
  • Experience with AI/ML and deep learning-based prediction model development
  • Experience working with/studying Electrocardiogram (ECG) and physiological signals using signal processing
  • Medical device industry experience
  • Excellent communication and collaboration skills

Responsibilities

  • Develop deep learning models to predict cardiac events using ECG and other physiological signals
  • Apply signal processing techniques to clean, analyze, and interpret biosignals for device diagnostics and monitoring
  • Support the design of AI/ML algorithms that enhance implantable device performance and patient outcomes
  • Collaborate with engineers to integrate Python-based tools for data analysis, simulation, and model validation
  • Contribute to feasibility studies exploring novel diagnostic features for heart rhythm detection
  • Analyze large datasets from implantable devices to identify patterns and inform next-generation therapy development
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