Description
Join our team of data scientists at Thermo Fisher Scientific, where you'll contribute to innovation through advanced analytics and AI solutions. As a Scientist II in Data Sciences, you'll apply technologies to solve complex business challenges across our organization. You'll work on diverse projects ranging from predictive modeling and machine learning to generative AI applications, collaborating with teams to deliver solutions that advance our mission of enabling customers to make the world healthier, cleaner, and safer.
In this role, you'll work with senior scientists, engineers, and software teams to build datasets, models, and workflows that support practical digital twin applications. The successful candidate will bring solid bioprocess knowledge, strong quantitative skills, and the ability to turn scientific questions into clear analyses and useful modeling results. This position offers professional growth opportunities and the chance to work with skilled professionals in a collaborative environment focused on innovation.
Responsibilities
- Support development of predictive modeling and simulation workflows for CHO cell culture and upstream bioprocess digital twin applications.
- Build, test, and evaluate models for key upstream process behaviors, including nutrient consumption, metabolite accumulation, cell growth, viability, and productivity.
- Analyze bioprocess datasets, including time-series bioreactor data, offline assay results, spent media data, and process metadata.
- Use Python and scientific computing tools to process data, run simulations, visualize results, and support model evaluation.
- Collaborate with scientists, engineers, and software developers to summarize modeling results, document assumptions, and support experimental planning.
Education
- Master's Degree in Biochemical Engineering, Chemical Engineering, Biotechnology, Computational Biology, Systems Biology, Bioinformatics, Cell Biology, or a related field; or Bachelor's Degree plus 2 years of industry experience.
Qualifications & Experience
- Relevant academic or industry experience in upstream bioprocessing, cell culture, process modeling, computational biology, data science, or related scientific domains.
- Good understanding of CHO cell culture and upstream bioprocessing concepts, including media, feeding strategies, bioreactor operation, metabolites, cell growth, viability, productivity, and process parameters.
- Hands-on Python experience for scientific computing, data analysis, visualization, simulation, or model implementation.
- Experience working with bioprocess or biological datasets, especially time-series data, assay results, spent media data, or process metadata.
- Familiarity with mechanistic, statistical, machine learning, or hybrid modeling approaches for biological or process systems.
- Strong analytical and problem-solving skills, with attention to data quality and scientific detail.
- Ability to work effectively in cross-functional teams and contribute to project activities under guidance from senior scientists or project leads.
Preferred
- Familiarity with PAT systems, bioreactor data infrastructure, LIMS/ELN/MES environments, cloud-based data workflows, or software-enabled scientific tools is a plus.
- Exposure to digital twin modeling, virtual experimentation, metabolic modeling, or process simulation is a plus.
