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

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).