Postdoctoral Data Analytics Computational Sciences

Johnson & Johnson Johnson & Johnson · Pharma · Spring House, PA +1

Postdoctoral researcher for application of advanced AI/ML methods to microscopic images of clinical and preclinical histopathology. Focus on application and refinement of deep learning algorithms to quantitate histopathology, and implementation of novel state-of-the-art techniques. Improve understanding of cellular organization and tissue structure to enhance clinical trial efficacy and efficiency.

What you'd actually do

  1. Conceive, design, develop, implement and validate innovative computer vision solutions addressing high-priority challenges in microscopy.
  2. Collaborate closely both with internal and external cross-functional teams of scientists, engineers, and clinicians, to advance algorithm and product development to improve project outcomes.
  3. Shape internal and external collaborations and define scope of research questions
  4. Clearly communicate complex technical methodologies and present findings to diverse audiences and stakeholders to support informed decision-making.
  5. Extract insight from complex, unstructured microscopy images to improve drug discovery and healthcare (e.g., disease identification, patient stratification, disease insights, therapy response).

Skills

Required

  • Ph.D. degree completed with in 2-3yrs, or Ph.D. candidate with a confirmed defense date within 3 - 4 months. in a field related to deep learning, such as computer science, physics, mathematics, applied mathematics, computer science/artificial intelligence, or related engineering disciplines.
  • Demonstrated deep experience researching and applying state-of-the-art computer vision techniques (e.g., Transformers, CNNs, RNNs, GANs, foundation models /self-supervision, panoptic segmentation, weakly supervised learning, few/zero-shot learning, etc)
  • Demonstrated experience in classical machine learning methods such as random forests, SVMs, etc.
  • Extensive experience applying, extending, and optimizing traditional image processing mathematics and methods (edge detection, thresholding, color transformations, morphological processing, etc)
  • Experience with microscopy images such as histopathology, confocal, or fluorescence microscopy.
  • Strong proficiency in Python and a related deep learning library (tensorflow, pytorch).
  • Fluent in English.
  • Strong communication & interpersonal skills.
  • Ability to work in a matrix organization and participate effectively both independently and as part of multiple teams.
  • Capacity to work under strict timelines.

Nice to have

  • Experience with multimodal AI.
  • Familiarity with drug discovery and clinical development processes.
  • Experience working closely with healthcare professionals.
  • Experience with meaningful disease biology in oncology, immunology, neuroscience, cardiovascular, or infectious disease.

What the JD emphasized

  • Strong publication record with the ability to effectively communicate technical work to a broad audience.
  • Demonstrated deep experience researching and applying state-of-the-art computer vision techniques
  • Experience with microscopy images such as histopathology, confocal, or fluorescence microscopy.

Other signals

  • application and refinement of J&J’s deep learning algorithm portfolio
  • implementation of novel state of the art techniques
  • application of advanced AI/ML methods to microscopic images of clinical and preclinical histopathology