At a Glance
- Tasks: Design and implement AI/ML methods for video understanding in medical applications.
- Company: Join Johnson & Johnson, a leader in global healthcare innovation.
- Benefits: Competitive salary, remote work options, and opportunities for professional growth.
- Other info: Collaborate with clinicians and engineers in a dynamic, supportive environment.
- Why this job: Make a real impact on healthcare by developing cutting-edge AI tools.
- Qualifications: Ph.D. in a quantitative field and experience in computer vision techniques.
The predicted salary is between 40000 - 55000 £ per year.
Janssen develops treatments that improve the health of people worldwide. Our research spans 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.
We are seeking highly skilled and motivated Postdoctoral Researchers to join our Video Understanding team at Johnson & Johnson. In this role, you will design, implement, and evaluate state‑of‑the‑art AI/ML methods for frame‑level and video‑level understanding across diverse medical modalities, including endoscopy, ultrasound, and magnetic resonance enterography (MRE). Your work will specifically focus on developing robust uncertainty models and multi‑modal architectures to extract reliable, high‑confidence insights from clinical data. You will collaborate closely with clinicians, engineers, and data scientists to translate these advanced algorithms into robust, interpretable, high‑impact tools that optimize decision‑making within clinical trial efficacy and workflows. Positions are available in the US (Titusville, NJ; Raritan, NJ; La Jolla, CA; Cambridge, MA; New York, NY; Spring House, PA) or Europe (UK, Netherlands, Switzerland, Austria). Remote arrangements will also be considered.
Key Responsibilities:
- Conceive, develop, and implement ideas with key internal clinical personnel to understand needs and use cases around AI tools for endoscopy.
- Design, develop, and evaluate deep learning models for medical video and image understanding (scoring, segmentation, and detection).
- Lead the research and development of uncertainty quantification methods for model predictions (e.g., Bayesian approaches, ensembles, calibration metrics, and predictive intervals) and integrate uncertainty estimates to quantify the reliability and confidence of AI‑driven diagnostic model outputs.
- Develop advanced multi‑modal models for video analysis, integrating data from endoscopy, ultrasound, intestinal ultrasound (IUS), and Magnetic Resonance Enterography (MRE).
- Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision‑making.
- Participate in cross‑functional team meetings, drive discussion and follow‑up questions to collaborators, and compile answers into briefing reports.
- Extract insights from collection of briefing reports focusing on business value of AI pipelines for immunology.
Required Qualifications:
- A Ph.D. degree in a quantitative discipline (e.g., Physics, mathematics, computer science, electrical engineering, or similar).
- Demonstrated experience driving research in and applying Computer Vision techniques (e.g., Transformers, CNNs, RNNs, GANs).
- Proven expertise in uncertainty model and measures development, including techniques for uncertainty quantification in deep learning.
- Demonstrated experience on state‑of‑the‑art techniques for video understanding (e.g., foundational models, transformers).
- Proficiency with one or more programming language 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.
- Strong publication record and ability to effectively communicate technical work to a wide audience.
Preferred Qualifications:
- Domain knowledge and experience with medical videos such as endoscopy.
- Experience with medical imaging modalities including ultrasound, intestinal ultrasound (IUS), and Magnetic Resonance Enterography (MRE) is good to have.
- Experience applying or adapting foundation/self‑supervised pretraining for medical domains (e.g., DINOv2, contrastive methods).
- Familiarity with clinical trial workflows, regulatory considerations, and working with clinical partners.
- Experience with multimodal AI; Familiarity with and exposure to drug discovery and clinical development processes.
- Experience working closely with healthcare professionals.
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.
Postdoctoral Researcher Video team employer: Johnson & Johnson
At Johnson & Johnson, we are committed to fostering a collaborative and innovative work environment that empowers our employees to make a meaningful impact on global health. As a Postdoctoral Researcher in our Video Understanding team, you will have access to cutting-edge resources and the opportunity to work alongside leading experts in the field, driving advancements in AI/ML for medical applications. Our inclusive culture prioritises professional growth, offering numerous pathways for career development while contributing to life-changing healthcare solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Postdoctoral Researcher Video team
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at Johnson & Johnson. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a presentation that highlights your best work in AI/ML methods and video understanding. This will help you stand out during interviews and discussions.
✨Tip Number 3
Practice makes perfect! Get comfortable discussing your research and technical methods. You’ll need to explain complex ideas clearly to diverse audiences, so practice with friends or colleagues.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team at Johnson & Johnson.
We think you need these skills to ace Postdoctoral Researcher Video team
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to highlight your relevant experience in AI/ML and video understanding. We want to see how your skills align with the role, so don’t be shy about showcasing your expertise in deep learning models and uncertainty quantification!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about the Video Understanding team and how your background makes you a perfect fit. We love seeing enthusiasm and a clear connection to our mission.
Showcase Your Research Impact:When detailing your research experience, focus on the impact of your work. Highlight any publications or projects that demonstrate your ability to communicate complex ideas effectively. We’re looking for candidates who can articulate their findings to diverse audiences!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way to ensure your application gets into the right hands. Plus, we love seeing candidates who take the initiative to engage directly with us.
How to prepare for a job interview at Johnson & Johnson
✨Know Your Stuff
Make sure you brush up on the latest AI/ML methods, especially those related to video understanding and uncertainty quantification. Be ready to discuss your previous research and how it aligns with the role at Johnson & Johnson.
✨Showcase Your Collaboration Skills
Since this role involves working closely with clinicians and engineers, prepare examples of past collaborations. Highlight how you’ve effectively communicated complex technical concepts to non-technical audiences.
✨Prepare for Technical Questions
Expect in-depth questions about your experience with deep learning models and computer vision techniques. Be ready to explain your approach to developing robust uncertainty models and how you would apply them in a clinical setting.
✨Ask Insightful Questions
Demonstrate your interest in the role by asking thoughtful questions about the team’s current projects or challenges they face in integrating AI tools into clinical workflows. This shows you’re not just interested in the position but also in contributing to their mission.