Are you eager to tackle cutting-edge challenges at the intersection of computational modeling, data science, and bioprocess optimization? Join Michael Betenbaugh's research lab to develop and refine some of the most sought-after research skills in both academia and industry. We are seeking a highly motivated and skilled Postdoctoral Researcher to lead a project focused on data-driven modeling, AI-assisted bioprocess optimization, and database development for CHO cell bioproduction. This project will involve genomic-scale metabolic modeling, kinetic modeling, AI-driven analytics, and the creation of a structured database to enhance the understanding and control of monoclonal antibody (mAb) production in CHO and HEK cell lines. A Ph.D. in Chemical Engineering, Systems Biology, Computational Biology, or a related field is desired. Johns Hopkins provides an exceptional research environment, fostering innovation at the interface of biomolecular engineering, computational biology, and biopharma. Why Join Us? - Collaborate with top-tier industry partners in biopharma and biotech through the Betenbaugh Lab's extensive network. - Be part of AMBIC, a leading biomanufacturing center, where you will have access to conferences, workshops, and seminars (Prof. Betenbaugh serves as the Center Director). - Mentorship & career development - Regular one-on-one meetings with Dr. Betenbaugh and collaboration with experts in the field. - Competitive standard benefits, with a highly supportive and interdisciplinary research environment. - Lab alumni have secured positions at numerous current and emerging biotech startups. - Baltimore offers an affordable and vibrant East Coast city experience with access to premier research and healthcare institutions. - Initial appointment for one year, with an expectation of at least two years total. Key Responsibilities: - Conduct literature reviews on genomic-scale metabolic modeling, kinetic modeling, and AI-driven bioprocess optimization. - Develop data-driven models to predict and optimize CHO and HEK cell culture performance. - Apply machine learning and statistical modeling techniques to enhance process control and decision-making in bioprocessing. - Perform flux balance analysis (FBA), kinetic simulations, and multi-omics data integration to refine metabolic models. - Design, develop, and maintain a structured database for CHO cell metabolism and bioprocessing data, integrating transcriptomics, proteomics, and metabolomics datasets. - Implement database management systems to improve accessibility and usability of CHO bioprocessing data. - Analyze and interpret large-scale bioprocessing datasets, ensuring data integrity and standardization. - Develop computational pipelines for automated data processing, metabolic flux analysis, and AI-assisted modeling. - Maintain detailed documentation of methodologies, workflows, and results, and communicate findings with industrial collaborators. - Prepare and present research findings through journal articles, conference presentations, and internal reports. - Assist in mentoring graduate students and junior researchers in computational modeling, data science, and database development. + PhD in Chemical Engineering, Biological Sciences, Bioengineering, or a related field + Background in bioprocess development and biomanufacturing optimization + Experience with mathematical modeling, and machine learning techniques. + Proficiency in data analysis, statistical modeling, and experimental design. - Proficiency in Python and Matlab Ability to work collaboratively in a multidisciplinary team environment. Salary: 62,000 In Interfolio, applicants should upload a CV and cover letter detailing their research experience and interests, and contact information for three references. The statement should state why the Betenbaugh lab is a good fit for your career trajectory. Job Type: Full Time The listed salary range represents the minimum and maximum Johns Hopkins University offers for this position, based on a good faith estimate at the time of posting. Actual compensation will vary depending on factors such as location, skills, experience, market conditions, education, and internal equity. Not all candidates will qualify for the highest salary in the range. Johns Hopkins provides a comprehensive benefits package supporting health, career, and retirement. Learn more: https://hr.jhu.edu/benefits-worklife/. Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. EEO is the Law https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf