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- Aufgaben: Lead AI integration in clinical workflows, focusing on PACS and oncology imaging.
- Arbeitgeber: Join an innovative MedTech company revolutionizing medical imaging with AI solutions.
- Mitarbeitervorteile: Enjoy a permanent position with immediate start and impactful work in healthcare.
- Warum dieser Job: Make a real difference in patient outcomes while collaborating with top professionals in the field.
- Gewünschte Qualifikationen: 3-5+ years in AI for medical imaging; expertise in PyTorch, GCP, and PACS required.
- Andere Informationen: Ideal for those passionate about improving healthcare through technology.
Das voraussichtliche Gehalt liegt zwischen 48000 - 84000 € pro Jahr.
Our client, an extremely innovative MedTech company, specializes in AI-powered solutions for medical imaging within the oncology field. As they prepare to initiate clinical trials, they seek a highly skilled Machine Learning AI Medical Imaging Expert to focus on clinical integration and PACS (Picture Archiving and Communication System) in support of diagnostic imaging within oncology.
Position Summary:
In this role, you will play a pivotal role in advancing the integration of AI systems into clinical workflows, with PACS as a primary focus. You will leverage machine learning expertise, specifically in Pytorch and Google Cloud Platform (GCP) , to support clinical trials and ensure seamless integration of AI imaging solutions. With models ready and segmentation as the next phase, your work will directly impact patient outcomes by supporting healthcare professionals in the efficient and accurate handling of medical imaging.
Key Responsibilities:
- Clinical Integration: Lead the integration of AI and machine learning models with PACS and other hospital information systems (e.g., EHR, RIS) to ensure smooth clinical workflows.
- Machine Learning Model Deployment: Apply your knowledge of machine learning in PyTorch and GCP to deploy and manage AI models focused on oncology imaging, emphasizing segmentation.
- PACS Management: Oversee the effective storage, retrieval, management, and secure sharing of digital images within the PACS, ensuring full system integration with patient health records.
- Collaboration with Clinical Teams: Act as a key collaborator with radiologists, oncologists, and technical teams to optimize model performance and align AI solutions with clinical needs.
- Data Integrity & Compliance: Maintain high standards for data integrity, security, and compliance, aligning with healthcare regulations and best practices.
- Innovation in Medical Imaging: Contribute to the development and refinement of machine learning techniques that enhance image processing, segmentation, and predictive analytics in oncology care.
Qualifications:
- Experience: 3-5+ years in AI and machine learning applications within medical imaging, with a focus on oncology.
- Technical Skills: Proficiency in PyTorch, GCP, and PACS integration; experience with clinical imaging systems and workflows.
- Soft Skills: Highly collaborative, humble, and team-oriented with a strong commitment to improving patient outcomes.
- Education: Degree in Computer Science, Data Science, Biomedical Engineering, or a related field.
Position: Machine Learning Engineer
Contract: Permanent
Start Date: Immediately or by agreement
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Machine Learning Engineer (AI Medical Imaging) Arbeitgeber: Panda International
Kontaktperson:
Panda International HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Machine Learning Engineer (AI Medical Imaging)
✨Tip Number 1
Familiarize yourself with the specific clinical workflows and systems used in oncology. Understanding how PACS integrates with EHR and RIS will give you a significant advantage during interviews, as you'll be able to discuss practical applications of your skills.
✨Tip Number 2
Showcase your experience with PyTorch and Google Cloud Platform by preparing examples of past projects where you've successfully deployed machine learning models. Be ready to discuss the challenges you faced and how you overcame them.
✨Tip Number 3
Highlight your collaborative skills by preparing anecdotes that demonstrate your ability to work effectively with clinical teams. Emphasizing your communication skills and teamwork will resonate well with the hiring managers.
✨Tip Number 4
Stay updated on the latest trends and innovations in AI medical imaging, particularly in oncology. Being knowledgeable about current advancements will not only impress interviewers but also show your passion for the field.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Machine Learning Engineer (AI Medical Imaging)
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the key responsibilities and qualifications required for the Machine Learning Engineer position. Tailor your application to highlight your relevant experience in AI, machine learning, and medical imaging.
Highlight Technical Skills: Emphasize your proficiency in PyTorch, Google Cloud Platform (GCP), and PACS integration in your CV and cover letter. Provide specific examples of projects or experiences where you successfully applied these skills, especially in the context of oncology.
Showcase Collaboration Experience: Since collaboration with clinical teams is crucial for this role, include examples of how you've worked with healthcare professionals, such as radiologists or oncologists, to optimize AI solutions. This will demonstrate your ability to work effectively in a team-oriented environment.
Focus on Impact: In your application, discuss how your work has positively impacted patient outcomes or improved clinical workflows. Use quantifiable results if possible to illustrate your contributions to previous projects in medical imaging or related fields.
Wie du dich auf ein Vorstellungsgespräch bei Panda International vorbereitest
✨Showcase Your Technical Skills
Be prepared to discuss your experience with PyTorch and Google Cloud Platform. Highlight specific projects where you've successfully deployed machine learning models, especially in the context of medical imaging.
✨Understand Clinical Workflows
Familiarize yourself with PACS and how it integrates with clinical systems like EHR and RIS. Demonstrating knowledge of these workflows will show that you can effectively contribute to the integration of AI solutions in a clinical setting.
✨Emphasize Collaboration
Since this role involves working closely with radiologists and oncologists, be ready to share examples of how you've collaborated with clinical teams in the past. Highlight your ability to communicate complex technical concepts in an understandable way.
✨Focus on Patient Outcomes
Discuss how your work in machine learning has positively impacted patient care. Be specific about how your contributions have led to improved diagnostic accuracy or efficiency in medical imaging processes.
