CMC Biologics Drug Substance Intern - Cell Culture Development; PhD

Company Description

Abb Vie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about Abb Vie, please visit us  Follow @abbvie onX,Facebook,Instagram,You Tube,Linked Inand Tik  Tok.

Job Description

Envision spending your summer working with energetic colleagues and inspirational leaders, all while gaining world-class experience in one of the most dynamic organizations in the pharmaceutical industry. This is a reality for Abb Vie Interns.

The CMC Biologics Drug Substance organization is a team of scientists driving scientific excellence and process development through innovative solutions. They are responsible for all Chemistry, Manufacturing, and Control (CMC) cell line and bioprocess development activities for Abb Vie's early-stage and late-stage products. As an intern, you will have the opportunity to learn and work on key aspects of developing fundamental scientific understanding related to Abb Vie's projects and processes, including exposure to innovative projects like applying machine learning (ML) techniques to build predictive models for our cell culture processes and improve our process development workflow.

Key responsibilities include:

• Develop and implement ML methodologies to build a hybrid model for predicting optimal outcomes in our cell culture processes.
• Exercise significant independence in selecting modeling approaches, frameworks, and evaluation strategies for establishing a predictive hybrid model.
• For the duration of the internship, take co-ownership of the project’s modeling life cycle, from data exploration and feature engineering to model validation and interpretation of the results.
• If time permits, collaborate with senior scientists to design and execute cell culture experiments to generate data for model refining and additional model validation.
• Present findings and progress to the department, effectively communicating methodologies, results, and potential impacts.
• Learn and understand various aspects of cell culture process development, integrating computational approaches to enhance timelines and outcomes.

Qualifications

Minimum Qualifications

• Currently enrolled in university, pursuing PhDin Computer Science, Statistics and Applied Mathematics, Computational Biology, Bioinformatics, Chemical Engineering, Data Science, or other related fields.
• Solid understanding of ML methodologies, ML frameworks (e.g., Sci-kit Learn, Tensor Flow, PyTorch), and statistical methods.
• Demonstrate programming competency for model implementation in Python or an equivalent language.
• Must be enrolled in university for at least one semester following the internship.

Preferred Qualifications

• Expected graduation date between December 2026 – Dec 2027.
• Prior experience in developing and implementing ML models for biological data is highly desirable. Applied modeling experience from your own academic research or lab projects that go beyond standard coursework.
• Proficiency with data visualization tools such as Matplotlib or Plotly to communicate model findings is a plus.
• Effective writer and communicator with ability to interact effectively with interdisciplinary scientists and engineers.
• High attention to detail, creativity in problem solving, strong interpersonal skills.

Additional Information

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:

Benefits and Amenities:

• Competitive pay

• Relocation support for eligible students

• Select wellness benefits and paid holiday / sick time

• Break rooms stocked with complimentary coffee, tea, beverages, snacks, and cold breakfast items.

• Onsite café and fitness center.

• The compensation range described below is the range of possible base pay compensation that the Company believes ingood faith it will pay for this role at the timeof this posting based on the job grade for this…