Postdoctoral Fellow BioProcess R&D
- Pfizer Inc.
- Location: Andover, MA
- Job Number: 7146438 (Ref #: 4885245)
- Posting Date: May 22, 2023
- Salary / Pay Rate: $80-$100K
- Application Deadline: Open Until Filled
Job Description
WHY PATIENTS NEED YOU
Pfizer’s purpose is to deliver breakthroughs that change patients’ lives. Research and Development is at the heart of fulfilling Pfizer’s purpose as we work to translate advanced science and technologies into the therapies and vaccines that matter most. Whether you are in the discovery sciences, ensuring drug safety and efficacy or supporting clinical trials, you will apply cutting edge design and process development capabilities to accelerate and bring the best in class medicines to patients around the world.
ROLE SUMMARY
A postdoctoral fellow position is available in the upstream process development group. This position will primarily focus on developing innovative mathematical models and computational tools to characterize, understand, and predict performance of biological systems used for production of biologics including mRNA and recombinant protein vaccines/therapeutics. The individual will also be performing experiments to generate data required for model training and validation. As appropriate, the individual uses omics and systems biology approaches to characterize biological systems for mathematical model development and training. The job function requires sound scientific judgment and innovation, using advanced practices and procedures to achieve solutions. This position is ideal for someone with expertise in machine learning, deep learning, kinetic modeling, mammalian central metabolism, glycosylation, and mRNA synthesis.
ROLE RESPONSIBILITIES
Builds hybrid (mechanistic + statistical) mathematical models for mRNA synthesis in invitro transcription processes and recombinant protein production in mammalian cell culture processes.
Conducts miniature to lab scale bioreactor experimentation to generate appropriate data to estimate/fit model parameters. Applies scientific and technical experience to design and execute experimentation for model parameter estimation.
Employs deep learning and machine learning techniques to fit model parameters using current and historical experimental data.
As appropriate, designs and conducts bioreactor and shake-flask experiments to generate transcriptomics, metabolomics, and other omics data for cell culture model construction and training.
Validates the models using experimentation and employs validated models to perform in silico analysis to probe, understand and characterize process parameter effect on biologic production.
Ensures effective, high-quality, timely and appropriate documentation in electronic laboratory notebooks and internal technical reports.
Presents data/strategy to scientists and management in appropriate internal and external venues (technical meetings, project team meetings, conferences etc.) and publishes in peer-reviewed journals, as appropriate.
Demonstrates leadership and capability to mentor junior colleagues, and fosters a team environment.
QUALIFICATIONS
Basic Qualifications
PhD degree in Chemical/Biochemical Engineering, Bioengineering, Biotechnology, Cell Biology, Microbiology with 0-3 years of relevant post-doctoral experience in academia or biotechnology/biopharma industry.
At least 1 first-author publication (published or manuscripts submitted for publication) in high-quality specialty or general readership journals.
A strong background in mathematical modeling, chemical/biochemical reaction kinetics, machine learning and deep learning techniques. The candidate should have significant experience in modeling complex biological systems.
The candidate should be self-motivated, organized, and capable of working independently and in a collaborative environment and should have demonstrated ability to drive modeling projects by coming up with innovative strategies.
The candidate should possess strong oral and written communication skills.
Preferred Qualifications
The candidate should have demonstrated proficiency in compiling and executing scripts in multiple computing environments including, but not limited to, MATLAB, Python, R and/or Perl, etc.
The candidate should have a good understanding of biochemical reactions involved in DNA transcription/mRNA synthesis and/or mammalian energy metabolism/glycosylation pathways.
The candidate has experience in employing functional analysis tools to analyze omics data and should have demonstrated ability to integrate such analyses with mathematical modeling.
The candidate should have strong attention to detail and has ability to execute detailed experimental plans, record procedures, analyze data, and present results.
PHYSICAL/MENTAL REQUIREMENTS
Position requires occasional light lifting and periods of standing, sitting or walking.
NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS
Occasional weekend work required.
OTHER JOB DETAILS
Must Have Work Authorization in US
Eligible for Relocation Assistance
Work Location Assignment: Flexible
Pfizer’s purpose is to deliver breakthroughs that change patients’ lives. Research and Development is at the heart of fulfilling Pfizer’s purpose as we work to translate advanced science and technologies into the therapies and vaccines that matter most. Whether you are in the discovery sciences, ensuring drug safety and efficacy or supporting clinical trials, you will apply cutting edge design and process development capabilities to accelerate and bring the best in class medicines to patients around the world.
ROLE SUMMARY
A postdoctoral fellow position is available in the upstream process development group. This position will primarily focus on developing innovative mathematical models and computational tools to characterize, understand, and predict performance of biological systems used for production of biologics including mRNA and recombinant protein vaccines/therapeutics. The individual will also be performing experiments to generate data required for model training and validation. As appropriate, the individual uses omics and systems biology approaches to characterize biological systems for mathematical model development and training. The job function requires sound scientific judgment and innovation, using advanced practices and procedures to achieve solutions. This position is ideal for someone with expertise in machine learning, deep learning, kinetic modeling, mammalian central metabolism, glycosylation, and mRNA synthesis.
ROLE RESPONSIBILITIES
Builds hybrid (mechanistic + statistical) mathematical models for mRNA synthesis in invitro transcription processes and recombinant protein production in mammalian cell culture processes.
Conducts miniature to lab scale bioreactor experimentation to generate appropriate data to estimate/fit model parameters. Applies scientific and technical experience to design and execute experimentation for model parameter estimation.
Employs deep learning and machine learning techniques to fit model parameters using current and historical experimental data.
As appropriate, designs and conducts bioreactor and shake-flask experiments to generate transcriptomics, metabolomics, and other omics data for cell culture model construction and training.
Validates the models using experimentation and employs validated models to perform in silico analysis to probe, understand and characterize process parameter effect on biologic production.
Ensures effective, high-quality, timely and appropriate documentation in electronic laboratory notebooks and internal technical reports.
Presents data/strategy to scientists and management in appropriate internal and external venues (technical meetings, project team meetings, conferences etc.) and publishes in peer-reviewed journals, as appropriate.
Demonstrates leadership and capability to mentor junior colleagues, and fosters a team environment.
QUALIFICATIONS
Basic Qualifications
PhD degree in Chemical/Biochemical Engineering, Bioengineering, Biotechnology, Cell Biology, Microbiology with 0-3 years of relevant post-doctoral experience in academia or biotechnology/biopharma industry.
At least 1 first-author publication (published or manuscripts submitted for publication) in high-quality specialty or general readership journals.
A strong background in mathematical modeling, chemical/biochemical reaction kinetics, machine learning and deep learning techniques. The candidate should have significant experience in modeling complex biological systems.
The candidate should be self-motivated, organized, and capable of working independently and in a collaborative environment and should have demonstrated ability to drive modeling projects by coming up with innovative strategies.
The candidate should possess strong oral and written communication skills.
Preferred Qualifications
The candidate should have demonstrated proficiency in compiling and executing scripts in multiple computing environments including, but not limited to, MATLAB, Python, R and/or Perl, etc.
The candidate should have a good understanding of biochemical reactions involved in DNA transcription/mRNA synthesis and/or mammalian energy metabolism/glycosylation pathways.
The candidate has experience in employing functional analysis tools to analyze omics data and should have demonstrated ability to integrate such analyses with mathematical modeling.
The candidate should have strong attention to detail and has ability to execute detailed experimental plans, record procedures, analyze data, and present results.
PHYSICAL/MENTAL REQUIREMENTS
Position requires occasional light lifting and periods of standing, sitting or walking.
NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS
Occasional weekend work required.
OTHER JOB DETAILS
Must Have Work Authorization in US
Eligible for Relocation Assistance
Work Location Assignment: Flexible
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer.
