PhD Summer Intern: Drug Product Development & AI/ML

Bristol-Myers Squibb Co

New Brunswick (NJ)

Presencial

USD 55 000 - 69 000

Tempo integral

Há 4 dias
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Vantagens oferecidas por esta oferta de emprego

Mentor program
Hands-on training
Formal presentation at internship end
Orientation and company overview

Resumo da oferta

Bristol-Myers Squibb Co. is seeking PhD candidates for a Summer Intern in Drug Product Development Engineering to advance predictive modeling and data science applications in pharmaceutical development.

The role involves designing computational models, applying ML/AI to datasets, and collaborating with formulation, process development, and device engineering teams. You will present findings in internal forums and gain valuable industry experience.

Qualificações

  • PhD candidate in engineering, materials science, computational sciences, or related quantitative field.
  • Must be enrolled during Summer 2027 and graduate between Fall 2027 and 2028.
  • GPA of 3.0 or greater on resume.
  • Strong communication and ability to work in a cross-functional team.
  • Experience in computational modeling and/or data science, ML/AI.
  • Programming experience in Python, MATLAB, or R.

Responsabilidades

  • Design and implement computational models for process variables and material properties.
  • Apply ML/AI to large datasets to drive insights and mitigate risks.
  • Collaborate with formulation, process development, and device engineering teams.
  • Present results to diverse audiences at internal forums.

Conhecimentos

Strong communication
Team collaboration
Problem solving

Formação académica

PhD candidate in engineering / materials science / computational sciences

Ferramentas

Python
MATLAB
R

Descrição da oferta de emprego

Bristol-Myers Squibb Co. is seeking PhD candidates for a Summer Intern in Drug Product Development Engineering to advance predictive modeling and data science applications in pharmaceutical development.

The role involves designing computational models, applying ML/AI to datasets, and collaborating with formulation, process development, and device engineering teams. You will present findings in internal forums and gain valuable industry experience.

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