Postdoctoral Fellow Purification Development
- Full-time
- Salary Min: 73000
- Salary Max: 138500
- Workday Global Grade: 15
Company Description
AbbVie'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 AbbVie, please visit us at www.abbvie.com. Follow @abbvie on X, Facebook, Instagram, YouTube, LinkedIn and Tik Tok.
Job Description
Purpose
We are seeking a highly motivated postdoctoral researcher to join our multidisciplinary team focused on developing a QSAR based modeling workflow to transform purification process development for complex biomolecules in our pipeline. This position offers an exciting opportunity to integrate chromatography, machine learning tools and analytical characterization to address one of the key challenges in biologics manufacturing - efficient process development of increasingly complex and diverse molecular constructs. The successful candidate will establish a robust dataset by performing chromatographic experiments on various industrially relevant molecules, use molecular modeling tools to generate descriptors and use machine learning tools to develop predictive models for these complex biomolecules and their impurities. In parallel, the researcher will collaborate closely with the protein engineering and analytical team to establish LC/MS workflows to gain molecular level insights into these complex molecules that will feed into the modeling workflow. The goal of this position is to generate a modeling framework and insight to inform molecular design strategies to help with developing facile purification processes for complex biomolecules. The candidate will also drive publications and presentations, externally and/or internally, related to the outcomes of this work
Responsibilities
- Design and conduct chromatography experiments to generate high quality data sets for machine learning model development.
- Apply machine learning and modeling techniques to extract insights to identify key process parameters and guide rational design of chromatographic steps.
- Collaborate with multidisciplinary teams to establish LC/MS workflows to characterize these complex molecules.
- Independently design, execute and interpret critical experiments to answer scientific questions, while seeking feedback from peers and supervisors.
- Understand the broad objectives of the project as well as their role in achieving those objectives, and modify experimental plan when required, to respond.
- Effectively organize and present scientific plans and data.
- Contribute to writing and conceptual framework of publications, presentations, and patents.
- Publish and disseminate data via external conferences and peer-reviewed publications.
Qualifications
- Successful completion and defense of a PhD. Minimum graduate school GPA 3.0; 3.5 preferred. Graduate of accredited and nationally ranked university
- Record of publication in a prestigious journal(s)
- Excellent problem-solving skills including critical and analytical thinking
- Excellent communication, leadership, and project management skills. Demonstrated scientific writing skills and strong verbal communication skills.
- Demonstrated ability to independently design and execute experiments, interpret data, and identify appropriate follow-up strategies.
- Proven track record of teamwork, adaptability, innovation, initiative, and integrity. Global mindset to thrive in a diverse culture and environment
- Ability to multitask and work within timelines.
Preferred Qualifications
- Successful completion of a PhD in Biochemistry, Chemical Engineering, Biotechnology or related fields. Graduate of accredited and nationally ranked university.
- Strong background in protein purification, chromatography and biophysical characterization preferably using LC/MS.
- Experience with data analysis, modeling, or machine learning methods is highly desirable.
- Record of publication in a prestigious journal(s).
Additional Information
- Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.
We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
This job is eligible to participate in our short-term incentive programs.
Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.
AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.
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