Data Science Intern working on computer vision for Johnson & Johnson's Innovative Medicine. Collaborating in a pharmaceutical environment to develop deep learning models for medical imaging.
Responsibilities
Design, develop, implement and validate innovative deep learning solutions addressing high-priority computer vision challenges in medical imaging.
Collaborate closely with cross-functional teams of scientists, engineers, and clinicians to advance algorithm and product development to improve project outcomes.
Clearly communicate complex technical methodologies and present findings to diverse audiences and stakeholders to support informed decision-making.
Prepare and draft manuscripts outlining development methodologies to contribute to the scientific community.
Requirements
Completion of Undergraduate Freshman year at an accredited University is required.
Actively pursuing a PhD in a field related to deep learning and computer vision, such as computer science, medical informatics, biomedical engineering, electrical engineering, or a related discipline.
Have a cumulative GPA of 2.8 or higher, which is reflective of all college coursework.
Strong publication record with the ability to effectively communicate technical work to a broad audience.
Publications in conferences such as CVPR, ICLR, ICCV, ICML, MICCAI, ACL, and NEURIPS are preferred but not mandatory.
Strong programming skills in Python and PyTorch.
Demonstrated solid foundation in applying deep learning techniques for computer vision and image analysis, particularly in object detection and image segmentation.
Experience working with histopathology data (whole slide images) is highly preferred.
Experience working with JSON and pandas is preferred.
Permanently authorized to work in the U.S., must not require sponsorship of an employment visa (e.g., H-1B or green card) at the time of application or in the future.
Students currently on CPT, OPT, or STEM OPT usually require future sponsorship for long term employment and do not meet the requirements for this program unless eligible for an alternative long-term status that does not require company sponsorship.
Benefits
Co-Ops/Interns are eligible to participate in Company sponsored employee medical benefits in accordance with the terms of the plan.
Co-Ops and Interns are eligible for the following sick time benefits: up to 40 hours per calendar year; for employees who reside in the State of Washington, up to 56 hours per calendar year.
Co-Ops and Interns are eligible to participate in the Company’s consolidated retirement plan (pension).
Head of Data Strategy leading and developing data initiatives for Zurich's GI Business. Focusing on data strategy, governance, and analytics while fostering collaboration across teams.
Medical Analyst analyzing engagement effectiveness with advanced analytics solutions aligned with Medical business strategies. Collaborating with cross - functional teams to provide insights for US Medical Affairs.
Research Fellow/Trainee in Women's Health using Data Science and Health Information Technology. Developing interdisciplinary research skills and methodologies focusing on health research.
Senior Data Scientist developing Asset Management Analytics for Queensland Rail. Contributing to organisational KPIs and enhancing asset performance through data analysis and modelling.
Senior Data Science Advisor providing data for business decisions and developing solutions. Role involves advanced analytics in the property and casualty insurance industry with a focus on model development.
Cientista de Dados Sênior na Deroyque, integrando a equipe e dominando o ciclo completo de Machine Learning. Transformando dados em decisões inteligentes em ambiente híbrido.
Data Scientist at LawDepot optimizing the Checkout experience through data - driven decisions. Involves statistical analysis, experiment design, and collaboration to enhance revenue growth.
Data Scientist leveraging data insights and machine learning for operational efficiency and innovation. Collaborate with stakeholders to drive impactful strategic decisions.
Data Scientist at Sun Life leveraging data and analytics to support client - centric solutions. Collaborating with business units to apply advanced analytics and drive measurable value.