Postdoctoral Data Analytics Computational… at Johnson &… · Remote

Summary: Johnson & Johnson is a leader in healthcare innovation, dedicated to developing treatments and cures. The role involves applying advanced AI/ML methods to microscopic images of clinical and preclinical histopathology, focusing on enhancing clinical trial efficacy and efficiency through innovative technologies. Responsibilities: - Conceive, design, develop, implement and validate innovative computer vision solutions addressing high-priority challenges in microscopy - 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 - Shape internal and external collaborations and define scope of research questions - Clearly communicate complex technical methodologies and present findings to diverse audiences and stakeholders to support informed decision-making - Extract insight from complex, unstructured microscopy images to improve drug discovery and healthcare (e.g., disease identification, patient stratification, disease insights, therapy response) - Prepare and draft manuscripts outlining development methodologies to contribute to the scientific community Required Qualifications: - 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. Equivalent experience will also be considered - 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 (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 Preferred Qualifications: - 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 Required Skills: Deep learning, Computer vision, Python Important Skills: Machine learning, Microscopy images Nice-to-Have Skills: Capacity to work under timelines Benefits: Medical, Dental, Vision, Life insurance, Short- and long-term disability, Business accident insurance, Group legal insurance, Company’s consolidated retirement plan (pension), Savings plan (401(k)), Vacation – up to 120 hours per calendar year, Sick time - up to 40 hours per calendar year; for employees who reside in the State of Washington – up to 56 hours per calendar year, Holiday pay, including Floating Holidays – up to 13 days per calendar year, Work, Personal and Family Time - up to 40 hours per calendar year