Intermediate Applied Machine Learning Scientist – Cancer Care AI Center of Excellence (COE) Siemens Healthineers

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Intermediate Applied Machine Learning Scientist – Cancer Care AI Center of Excellence (COE) Siemens Healthineers

Role Summary: The Intermediate Applied Machine Learning Scientist will design, develop, and deploy deep learning solutions for oncology imaging, with a strong emphasis on 3D medical image segmentation, domain adaptation, and adaptive radiotherapy workflows. This role focuses on translating cutting-edge AI research into clinically valuable tools that support radiation oncologists and improve precision in cancer care using CBCT, CT, and multimodal data.

Key Responsibilities Model Development & Technical Innovation:

• Develop and optimize 3D deep learning models for auto-segmentation of critical structures in cancer imaging on CBCT, CT, and other modalities, leveraging frameworks such as nnU-Net, TotalSegmentator, MedSAM, and similar tools.
• Implement domain adaptation, transfer learning, pseudo-label fusion, and synthetic-to-real techniques to improve model performance across multi-vendor clinical datasets.
• Build scalable pipelines for medical image preprocessing, exploratory data analysis, feature extraction, landmark detection (heatmap regression), and high-quality ground-truth dataset curation in collaboration with clinicians.

Clinical Integration & Validation:

• Advance adaptive radiotherapy applications, including treatment response prediction, dose-volume histogram analysis, and clinical validation using metrics such as Dice Similarity Coefficient (DSC) and AUROC.
• Ensure models meet regulatory, safety, and performance standards through rigorous experimentation and multi-site validation.
• Collaborate with radiation oncologists, radiologists, and cross-functional teams to translate clinical needs into robust, production-ready AI solutions.

Research & Collaboration:

• Contribute to publications, patents, and knowledge sharing while staying current with advances in medical AI.
• Work closely with clinical partners to refine tools based on user feedback and real-world performance.
• Support dataset harmonization and annotation pipelines to enable high-impact oncology AI development.

Knowledge, Skills, & Experience:

• The ideal candidate is a hands-on ML researcher with strong expertise in medical imaging and a passion for oncology applications.

• M.Sc. (or PhD) in Computer Science, Computing Science, Biomedical Engineering, Medical Imaging, or a related field.
• 1–3 years of applied deep learning experience in medical imaging, preferably in oncology, adaptive radiotherapy, or 3D segmentation.
• Strong proficiency in Python, PyTorch (TensorFlow/Keras a plus), nnU-Net workflows, medical imaging libraries (MONAI, SimpleITK), and tools such as TotalSegmentator and MedSAM.
• Experience curating clinical datasets, performing domain adaptation, and conducting rigorous validation (Dice, bootstrap CIs, etc.).
• Familiarity with DICOM data, multi-vendor CT systems (e.g., Siemens), and collaboration with clinical teams.
• Publications or demonstrated impact in medical AI preferred.
• Excellent communication and cross-functional collaboration skills.

Technical & Leadership Competencies:

• 3D Medical Imaging Expertise: Deep understanding of CBCT/CT segmentation, landmark detection, and adaptive radiotherapy pipelines.
• Technical Excellence: Strong problem-solving in domain adaptation, transfer learning, and production-oriented ML workflows.
• Clinical Focus: Ability to deliver solutions that provide measurable value to oncologists and patients.
• Collaboration & Communication: Works effectively with clinicians, engineers, and researchers; translates complex concepts for diverse stakeholders.
• Innovation & Rigor: Balances cutting-edge research with practical, validated clinical outcomes.
• Integrity & Quality: Committed to responsible AI, patient safety, and regulatory excellence.

This role offers a unique opportunity to drive transformative AI innovations in cancer care at Siemens Healthineers.

About the program:

You will be part of a transformative long-term partnership aimed at innovating cancer care delivery in Alberta. The Cancer Innovation Value Partnership (CIVP) brings together Siemens Healthineers’ world-class technologies, services, and consulting expertise to enable a more sustainable, precise, and patient-centric oncology pathway.

Learn more: https://www.siemens-healthineers.com/services/value-partnerships

Who we are: We are a team of more than 72,000 highly dedicated Healthineers in more than 70 countries. As a leader in medical technology, we constantly push the boundaries to create better outcomes and experiences for patients, no matter where they live or what health issues they are facing. Our portfolio is crucial for clinical decision-making and treatment pathways.

How we work: When you join Siemens Healthineers, you become one in a global team of scientists, clinicians, developers, researchers, professionals, and skilled specialists, who believe in each individual’s potential to contribute with diverse ideas. We are from different backgrounds, cultures, religions, political and/or sexual orientations, and work together, to fight the world’s most threatening diseases and enable access to care, united by one purpose: to pioneer breakthroughs in healthcare. For everyone. Everywhere. Sustainably.

To find out more about Siemens Healthineers' businesses, please visit our company page at Siemens Healthineers Canada.

The expected compensation for this position is:

$67,000 - $95,500

Factors which may affect starting compensation within this range may include geography/market, skills, education, experience, and other qualifications of the successful candidate.

Siemens Healthineers offers a variety of health and wellness benefits including a flexible benefits plan, Defined Contribution Pension Plan, Registered Retirement Savings Plan matching contributions, plus a competitive paid time off program including vacation, company holidays, sick leave, and parental leave (all subject to eligibility requirements).

This information is provided per required laws and regulations. Applicants should apply via Siemens Healthineers external or internal careers site.

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