Scientist III, Bioinformatics, Upstream Process Development Full-time

Bioinformatics Scientist

As part of the Thermo Fisher Scientific team, you'll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We are seeking to hire a highly motivated Bioinformatics Scientist with hands-on experience in data-driven cell culture media design. The successful candidate will join a multi-functional team and help support and bridge small-scale cell culture with machine learning and omics data interpretation, with a particular focus on CHO and HEK cells. The aim is to generate new solutions about upstream bioprocessing to guide the development of new cell culture products that support the commercial production of novel biologic therapeutics. Working in a collaborative environment, you'll contribute to innovative projects while supporting our mission of enabling customers to make the world healthier, cleaner, and safer.

What will you do?

• Leverage bioinformatics tools including machine learning models and metabolic flux analysis, and implement knowledge bases to provide actionable insights for cell culture media development and bioproduction process optimization.
• Provide bioinformatics support and manage multi-omics data integration, documentation, and report preparation for scientific services and research projects.
• Under minimal supervision, the successful candidate will be expected to perform data analysis on experimental data, interpret analysis results, and communicate and present findings in team meetings.
• Contribute to the development of innovative computational models and omics approaches to solve biological problems related to bioproduction processes.

How will you get here?

Education

• MS in Bioinformatics, Computational Biology, Cell Biology, or related field (PhD is preferred)

Experience

• At least three (3) years of related experience
• Experience in utilizing machine learning and statistical models.
• Experience in upstream process development including process and media optimization.
• Experience with pathway enrichment, network analysis and multi-omics integration and interpretation.
• Proficiency in programming languages such as Python or R

Knowledge, Skills, Abilities

• Strong understanding of statistical inference and machine learning techniques.
• Knowledge in molecular and cellular biology.
• Present data for review, group discussions, and team meetings
• Multi-task effectively and prioritize multiple projects with guidance.
• Proven track record that could work efficiently both independently and as part of a team.
• Excellent verbal and written communication skills.
• Ability to analyze, interpret and summarize scientific results in a clear, concise, and accurate manner.
• Ability to work in a cross-functional and interdisciplinary team.

Preferred Qualifications

• Statistical Design of Experiment (DOE) experience.
• Experience in HPLC-MS-based proteomics and metabolomics.

Compensation and Benefits

The salary range estimated for this position based in New York is $87,200.00–$116,200.00.

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:

• A choice of national medical and dental plans, and a national vision plan, including health incentive programs
• Employee assistance and family support programs, including commuter benefits and tuition reimbursement
• At least 120 hours paid time off (PTO), 10 paid holidays annually, paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave), accident and life insurance, and short- and long-term disability in accordance with company policy
• Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan
• Employees' Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount