Research Intern - Distributed Computing and Graph Computation in Machine Learning

Do you want to join us in helping to fight the world’smost threatening diseases and enabling access to care for more people aroundthe world? At Siemens Healthineers, we pioneer breakthroughs inhealthcare.  For everyone. Everywhere.

At Siemens Healthineers, we offer you a flexible anddynamic environment with opportunities to go beyond your comfort zone to growpersonally and professionally. Sound interesting? Then

come and join our global team as a Research Intern -Distributed computing and graph computation in Machine Learning.

Our global team: We are a team of 68,000 highly dedicatedemployees across more than 70 countries passionately pushing the boundaries ofwhat’s possible in healthcare to help improve people’s lives around the world.As a leader in the industry, we aspire to create better outcomes andexperiences for patients no matter where they live or what health issues theyare facing. Our portfolio, spanning from in-vitro and in-vivo diagnostics toimage-guided therapy and innovative cancer care, is crucial for clinicaldecision-making and treatment pathways.

Our culture: We are part of an incredible community ofscientists, clinicians, developers, researchers, professionals, and skilledspecialists pushing the boundaries of what’s possible, to improve people’slives around the world.  We embrace aculture of inclusivity in which the power and potential of every individual canbe unleashed. We spark ideas that lead to positive impact and continuedsuccess. Check our Careers Site at https://www.siemens-healthineers.com/en-us/careers.

This is a role well suited for a highly motivated student looking to build theirskill set and gain hands-on experience. As a research intern, you will beresponsible for:

• Developingtree/graph structures for efficient large-scale point cloud processing
• Developingdistributed computing frameworks in both GPU and/or CPU for non-learning andlearning approaches
• Optimizecomputational resources used in non-learning and learning approaches

This position may suit you best if you’re familiar withthe following and would like to develop your skills

with Siemens Healthineers:

• Proficiencyin Python and PyTorch programming
• Strong skillsand knowledge in tree/graph data structure implementation and processing inPython
• Proficiencyin implementing efficient distributing parallel computing in GPU/CPU fornon-learning and learning approaches
• Strongbackground in mathematics (preferred)
  • Skills inCUDA-PyTorch custom interface and blinding (preferred)
• Experience incomputer vision, medical image analysis, image processing, and imaging(preferred)

Required skills to have for the success of this role:

• Masteror PhD program majoring in Computer Science, Mathematics, Applied Mathematics,Electrical and Computer Engineering, or related fields.
• OR Currently enrolled in andpursuing studies at a foreign degree- or certificate-granting post-secondaryacademic institution outside the United States OR Has graduated from such aninstitution no more than 12 months prior to his or her exchange visitor programstart date (for J-1s)
• Minimum 3.0 GPA (preferred)

Start date: April2024

At SiemensHealthineers, we value those who dedicate their energy and passion to a greatercause. Our people make us unique as an employer in the med-tech industry. Whatunites and motivates our global team is the inspiration of our commonpurpose:  To innovate for healthcare,building on our remarkable legacy of pioneering ideas that translate into evenbetter healthcare products and services. We recognize that taking ownership ofour work allows both us and the company to grow. We offer you a flexible anddynamic environment and the space to move beyond your comfort zone to grow bothpersonally and professionally.

If you wish tofind out more about the specific division before applying, please visit:https://usa.healthcare.siemens.com/about.

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