At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com

JOB DESCRIPTION:

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.
Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.
Learn more at https://www.jnj.com/innovative-medicine
Johnson & Johnson’s Innovative Medicine - Research & Development (JRD) is seeking to recruit a Postdoctoral Scientist, for a fixed term of 2 years, specializing in Artificial Intelligence (AI) based solutions for Neuroimaging Data. The most preferred location for this position is Cambridge, Massachusetts USA or Beerse, Belgium. Remote work options may be considered on a case-by-case basis and if approved by the Company.

The AI/Machine Learning and Digital Health team within Johnson & Johnson Innovative Medicine R&D designs cutting-edge insights and solutions employing various data sources across multiple disease areas. We are in search of an exceptional postdoctoral scientist with key responsibilities:

• Design, develop, and implement cutting-edge AI and computer vision solutions to address high-priority scientific challenges in biomedical imaging. Your work will directly contribute to advancements in drug discovery and healthcare.
• Develop and optimize state-of-the-art models to extract actionable insights from complex, unstructured biomedical image data.
• Contribute to the development of scalable core technologies that enable the deployment of advanced computer vision solutions across a variety of imaging modalities, including radiology, and brain imaging.
• Develop and deploy models using containerization technologies such as Docker and Kubernetes to ensure scalable and efficient deployment in production environments.
• Utilize high-performance computing resources and techniques to manage and process large-scale datasets and complex models efficiently.
• Clearly articulate complex technical methods and results to diverse audiences, including scientists, stakeholders, and decision-makers, to facilitate informed decision-making and drive project success.
• Author scientific publication, patents, technical reports.

REQUIRED QUALIFICATIONS:

• A Ph.D. (completed within the past 3 years, or to be completed within the upcoming 6 months) in computer science, artificial intelligence, neuroscience, biomedical science, electrical engineering, biomedical engineering, biostatistics, statistics, mathematics, or related disciplines.
• Demonstrated experience in driving research in computer vision, including the application and development of AI methods and optimization of machine learning models.
• Proficiency in programming languages such as Python, R, C++, or Java, and with AI frameworks including PyTorch, and OpenCV.
• Extensive experience with traditional and modern computer vision techniques, including object detection (YOLO, SSD, Faster R-CNN), image segmentation (U-Net, Mask R-CNN), image classification (VGG, ResNet, Inception, EfficientNet), and feature extraction (SIFT, SURF, ORB).
• Experience with various machine learning techniques (including fully supervised, unsupervised, self-supervised, and weakly supervised learning) and specific architectures (Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), and attention-based networks)
• Strong understanding and experience with machine learning algorithms (such as random forests, SVMs, boosting, and neural networks) along with optimization techniques.
• Proficiency in statistical analysis and data handling, including data augmentation, data cleaning, normalization, and handling large-scale image datasets.
• Ability to effectively communicate complex technical concepts and results to a wide range of audiences, including non-technical stakeholders.
• Highly motivated and capable of driving projects forward independently with minimal daily oversight.
• Experience working with multi-GPU workloads for training and inference
• A deep passion for leveraging data and AI to drive scientific innovation and improve healthcare outcomes.
• Proven scientific excellence as evidenced by publications, patents, and high-level presentations.

PREFERRED QUALIFICATIONS:

• Hands-on experience in data AI solutions with focus on neuroimaging data (MRI, CT, PET, fMRI).
• Experience with high-performance computing techniques and resources to manage and process large-scale datasets and complex models efficiently.
• Familiarity with drug discovery, the clinical development process, and/or expertise in specific therapeutic areas.
• Experience with disease biology in areas such as cancer, immunology, neuroscience, cardiovascular, or infectious disease, enabling the development of targeted AI solutions.
  Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s):
  USA - Requisition Number: R-002263
  Belgium - Requisition Number: R-004759
  Remember, whether you apply to one or all of these requisition numbers, your applications will be considered as a single submission

• Design, develop, and implement cutting-edge AI and computer vision solutions to address high-priority scientific challenges in biomedical imaging. Your work will directly contribute to advancements in drug discovery and healthcare.
• Develop and optimize state-of-the-art models to extract actionable insights from complex, unstructured biomedical image data.
• Contribute to the development of scalable core technologies that enable the deployment of advanced computer vision solutions across a variety of imaging modalities, including radiology, and brain imaging.
• Develop and deploy models using containerization technologies such as Docker and Kubernetes to ensure scalable and efficient deployment in production environments.
• Utilize high-performance computing resources and techniques to manage and process large-scale datasets and complex models efficiently.
• Clearly articulate complex technical methods and results to diverse audiences, including scientists, stakeholders, and decision-makers, to facilitate informed decision-making and drive project success.
• Author scientific publication, patents, technical reports