Thermo Fisher Scientific Inc. is the world leader in serving science, with annual revenue exceeding $40 billion. Our mission is to enable our customers to make the world healthier, cleaner, and safer. Whether our customers are accelerating life sciences research, solving complex analytical challenges, improving patient diagnostics and therapies, or increasing productivity in their laboratories, we are here to support them.
This is an onsite position that can be hired in Grand Island, NY, Carlsbad, CA, or Hunt Valley, MD. Residency near these 3 sites is required. Relocation assistance is not provided.
How will you make an impact?
We are seeking a highly motivated Data Scientist with strong hands-on expertise in machine learning and deep learning (ML/DL), as well as mechanistic modeling, to join our interdisciplinary team. In this role, you will collaborate closely with experts in cell culture, multi-omics, and data science to develop and apply advanced hybrid modeling approaches that accelerate new cell culture product development and support media development services. This position offers the opportunity to work in a highly collaborative, innovation-driven environment while contributing to Thermo Fisher Scientific's mission to enable a healthier, cleaner, and safer world.
What will you do?
How will you get here?
Education
Experience
Knowledge, Skills, Abilities
Preferred Qualifications
Thermo Fisher Scientific is an EEO/Affirmative Action Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other legally protected status.
The salary range estimated for this position based in New York is $88,000.00–$116,000.00.
This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy. We offer a comprehensive Total Rewards package that our U.S. colleagues and their families can count on, which includes:
Tagged as: Life Sciences
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