Siemens Careers

Intern - Artificial Intelligence

Knoxville, Tennessee
Research & Development

English (US)

Job Description

Division: Siemens Healthineers
Business Unit: Diagnostic Imaging
Requisition Number: 238572
Primary Location: United States-Tennessee-Knoxville
Assignment Category: Part-time temporary
Experience Level: Entry level
Education Required Level: Bachelor's Degree
Travel Required: No

Division Description:

At Siemens Healthineers, we are passionate about enabling healthcare professionals to deliver high quality patient care, and to do so affordably.  A leading global healthcare company, Siemens Healthineers continues to strengthen our portfolio of medical imaging and laboratory diagnostics, while adding new offerings such as managed services, consulting, and healthcare IT services – as well as further technologies in the growing market for therapeutic and molecular diagnostics.


Siemens Healthineers develops innovations that support better patient outcomes with greater efficiencies, giving providers the confidence they need to meet the clinical, operational and financial challenges of a changing healthcare landscape.

Job Description:

Siemens Medical Solutions USA, Inc. is one of the largest global suppliers of healthcare equipment, renowned for innovative products, services and solutions including diagnostic imaging systems, therapy equipment for treatment and electro medicine and IT solutions to optimize workflow and increase efficiency in the healthcare industry.

We are working on next generation smart workflow, reading and reporting solutions used in molecular imaging (PET/CT, SPECT/CT, PET/MR). We are currently seeking a summer intern to join our pre-development team in Knoxville, TN.


The ideal candidate is a senior undergraduate or graduate student with excellent background in computer science. In this role, you will explore the applications of generative adversarial (GAN) models in the field of medical imaging (PET/CT). In particular, you will investigate the potential of GANs in the context of data augmentation, image to image translation and propose innovative concepts.


You will drive the evaluation of these concepts with the team and advocate your innovations. This position will provide our candidate with an excellent opportunity for visibility and impact, as you will be reporting directly to the Director of Clinical Applications in the Research and Clinical Collaborations department in our molecular imaging business line.



- Design and implement modules/algorithms

- Integrate your work in existing frameworks

- Perform validation of methods and algorithms


Required Knowledge/Skills, Education, and Experience

o    Ideal candidates should be senior undergraduate or graduate student in computer science.

o    Candidate should be proficient in Python.

o    Candidate should have extensive knowledge in deep learning


Preferred Knowledge/Skills, Education, and Experience

o    Prior experience with machine learning packages such as TensorFlow, Pytorch is preferred

o    Prior experience with Generative Adversarial networks is preferred

o    Prior experience with image/signal processing is preferred

o    Prior experience working in interdisciplinary teams is preferred



Equal Employment Opportunity Statement
Siemens is an Equal Opportunity and Affirmative Action Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, protected veteran or military status, and other categories protected by federal, state or local law.

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Applicants and employees are protected under Federal law from discrimination. To learn more, Click here.

Pay Transparency Non-Discrimination Provision
Siemens follows Executive Order 11246, including the Pay Transparency Nondiscrimination Provision. To learn more, Click here.

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