Post Doctoral Researcher
6 days ago
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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/.
For more than 130 years, diversity, equity & inclusion (DEI) has been a part of our cultural fabric at Johnson & Johnson and woven into how we do business every day. Rooted in Our Credo, the values of DEI fuel our pursuit to create a healthier, more equitable world. Our diverse workforce and culture of belonging accelerate innovation to solve the world's most pressing healthcare challenges.
We know that the success of our business - and our ability to deliver meaningful solutions - depends on how well we understand and meet the diverse needs of the communities we serve. Which is why we foster a culture of inclusion and belonging where all perspectives, abilities and experiences are valued and our people can reach their potential.
At Johnson & Johnson, we all belong.
The Data Science Analytics & Insights team is actively searching for a highly motivated and visionary post-doctoral researcher, with a primary research focus on Artificial Intelligence (AI) reasoning, problem solving, and natural language inferencing. We are particularly interested in candidates who possess a strong background in mathematics and a deep passion for making a meaningful impact through their work. In this role, you will play a crucial part in devising innovative Artificial Intelligence/Machine Learning (AI/ML) algorithms to extract valuable insights from vast structured and unstructured knowledge. Your contributions will involve developing sophisticated large language model (LLM) agents that excel in solving complex problems spanning areas across the pharmaceutical lifecycle.
Key Responsibilities:
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- Partner with research colleagues to develop, validate, and apply groundbreaking LLM-based methodologies to automate the planning and execution of solutions for scientific research challenges.
- Connect agents to multi-modal sources of data at scale - including unstructured text, structured tables, and images.
- Serve as a domain expert within the field by articulating to team members emerging approaches and methodologies within the AI domain (e.g. causal inferencing, reinforcement learning, attention models, etc.) with a clear understanding of their practical applications within the industry.
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