Senior Concept Development Engineer - Electrophysiology

Additional Location(s):  N/A

Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance

At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions.       

 

At Boston Scientific, you will find a collaborative culture driven by a passion for innovation that keeps us connected on the most essential level. With determination, imagination and a deep caring for human life, we’re solving some of the most important healthcare industry challenges. Together, we’re one global team committed to making a difference in people’s lives around the world. This is a place where you can find a career with meaningful purpose—improving lives through your life’s work.

 

About the role: 

Boston Scientific is a global medical technology leader for more than 35 years. Our mission at Boston Scientific is to transform lives through innovative medical solutions that improve the quality of patient care. The Waltham-based division is a small, dynamic, fast-growing part of Boston Scientific’s Electrophysiology Division with a highly talented team supporting the development of our EP portfolio. The high-resolution 3D maps of the electrical activity of the human heart provided by our cardiac mapping system are used by physicians to diagnose and treat cardiac arrhythmia.

 

The Concept Development Engineer is a high impact role, guiding the design and development of novel algorithms and tools for cutting-edge medical applications in the field of Cardiac Electrophysiology. The primary responsibilities include: ideating novel concepts, rapidly prototyping solutions, creating and analyzing technical data and communicating high level data-driven decisions.

 

Your responsibilities include:

• Develop engineering solutions and investigate competitive technologies related to Cardiac Electrophysiology
• Explore, model, and develop new algorithms to enhance mapping features including pattern recognition, multi-modality imaging, volumetric mesh manipulation
• Independently lead small research projects while collaborating with team members on larger initiatives
• Effectively collaborate across disciplines (HW, Software, Systems, and ME) to focus on and maximize end-to-end solution value
• Stay current with industry trends and new methodologies including artificial intelligence and machine learning
• Support the establishment and execution of detailed project plans and milestones to drive towards feasibility assessment.

 

 

Required qualifications:

• Master’s Degree in Biomedical Engineering/Computer Science/Electrical Engineering or equivalent with at least 2 years of product development experience in a commercial environment.
• Demonstrated expertise in MATLAB/Python or equivalent for prototyping, modeling and analysis
• Domain Expertise in Medical Imaging or applicable field
• Creative solution-oriented mindset
• Experience with Image processing and transformation models
• Strong knowledge of data structures, Applied Mathematics and Applied statistics
• Ability to work with ambiguity to balance risk and opportunity.
• Ability to scope and manage complex tasks in the 3–6-month timeframe
• Enthusiasm for collaborative work

 

Preferred qualifications:

• PhD in Biomedical Engineering/Computer Science with Signal/Image processing or Algorithm/Method Development background
• Experience with Image processing and transformation models
• Domain Expertise in Computer Vision Techniques
• Excellent communication and presentation skills, capable of conveying technical information in a clear and thorough manner
• Design and develop real-time algorithms to support geometry manipulation, meshing, mesh adaptation, and interactive 3D visualization tools
• Familiarity with lab equipment (signal generator, oscilloscope, LabView, etc.)
• Prior experience with optimization, inverse problems and machine learning techniques