Data Science Postdoc, Medical Imaging Computer Vision

• A Ph.D. degree in a field related to quantitative analysis, such as physics, mathematics, artificial intelligence, computer science, applied mathematics, electrical engineering, or similar. Equivalent experience will also be considered.


• Strong publication record and ability to effectively communicate technical work to a wide audience (CVPR, ICLR, ICCV, ICML, MICCAI, ACL, NEURIPS, etc..)


• Demonstrated experience driving research in and applying Computer Vision techniques (e.g., Transformers, CNNs, RNNs, GANs)


• Proven expertise in modern video comprehension techniques (e.g. foundational models, transformers)


• Proficiency with one or more programming languages such as Python or C++


• Extensive experience with traditional Computer Vision applications, such as OpenCV, object detection, edge detection, image segmentation


• Experience with machine learning algorithms, including random forest, SVM, boosting, neural networks, etc

Preferred Qualifications:

• Experience with medical videos such as endoscopy, ultrasound, echocardiogram; dermatology images as well as object character recognition (OCR) and medical imaging anonymization


• Experience with multimodal AI


• Familiarity with and exposure to drug discovery and clinical development processes


• Experience working closely with healthcare professionals


• Experience with meaningful disease biology in cancer, immunology, neuroscience, cardiovascular, or infectious disease

Thriving on a diverse company culture and celebrating the uniqueness of our employees, we are committed to inclusion. We are proud to be an equal opportunity employer.

Johnson & Johnson is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

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Janssen Research & Development LLC, a Johnson & Johnson company, is recruiting for a postdoc located in Vienna, Austria

Janssen develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, immunology, neuroscience, and infectious disease. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals. To learn more about Janssen, one of the Pharmaceutical Companies of Johnson & Johnson, visit www.janssenpharmaceuticalsinc.com.

We are looking for talented and driven individuals to join our Video Understanding team at Johnson & Johnson. As a postdoctoral researcher, you will have the exciting opportunity to contribute to the development and implementation of advanced AI/ML methods for medical video understanding. Your role will involve applying sophisticated AI techniques to extract valuable insights from different medical video modalities like endoscopy, ultrasound, and echocardiogram. Through the use of these innovative technologies, you will improve our understanding of medical procedures and interventions, ultimately enhancing clinical trial efficacy and efficiency.

The Data Science Analytics & Insights team within Janssen R&D develops innovative solutions using a variety of data sources across multiple different disease areas. We are looking for an outstanding postdoc with a focus on Radiology Computer Vision.

Key Responsibilities:

• Conceive, develop, and implement video understanding computer vision solutions to high-priority scientific problems


• Participate in cross-functional collaborations with external companies and internal scientific, clinical, and data science teams


• Shape internal/external collaborations and define the scope of research questions


• Extract insight from complex, unstructured medical image and videos to improve drug discovery and healthcare (e.g., disease identification, patient stratification, disease insights)


• Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making