Position Title: Postdoctoral Fellowship: Bioprocess Analytics
Location: Framingham, MA
We are looking for candidates for an exciting post doc position to join our Bioprocess analytics team. The ideal candidate will join a dynamic and PAT motivated team and will serve as a key subject matter expert supporting bioprocess process development, data analytics and statistics process control
We are looking for candidates for an exciting post doc position to join our Bioprocess analytics team. The ideal candidate will join a dynamic and PAT motivated team and will serve as a key subject matter expert supporting bioprocess process development, data analytics and statistics process control activities using vibrational spectroscopic technologies.
Major Job responsibilities:
Invisible to visible spectral characterizations of CQAs using pattern recognition, artificial intelligence, machine learning and established pleiotropic network of biomolecules.
Analyze large data sets which include real-time bioprocess data and offline analytical data sets.
Characterizations and interpretations of cell culture’s critical quality attributes (CQAs) and parameters using UV, Raman, FTIR, Imaging, florescence and FBRM spectroscopy.
Develop Chemometrics data analysis concepts and modeling in support of batch and continuous manufacturing.
Develop a Chemometrics predictive modeling platform, exploratory data analysis, Chemometrics model development, validation and model maintenance.
Basic Qualifications:
PhD from an accredited university in Process Spectroscopy, Chemometrics, chemical engineering or process engineering
Expertise in developing, interpreting, implementing and managing vibrational or other spectroscopic techniques such as FTIR, NIR, Raman, Imaging, florescence and FBRM or related techniques with a strong publication record
Strong expertise on Chemometrics data modeling combined with invisible to visible modeling concept using Bioprocess data
Expertise on machine learning, neural networks, clustering, pattern recognition, probability, supervised and unsupervised data modeling
Outstanding experience on upstream, downstream bioprocess and cell culture data mining
Expertise in analyzing mass spectrometric, chromatographic, thermal and genomic data analysis using machine learning and support vector machine
Advance skills with R, C++, and MATLAB/Simulink, and Neuron
Must have US work authorization
Preferred Qualifications:
PAT implementations in continuous manufacturing environment is plus
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