Job Description We are looking for an enthusiastic postdoctoral researcher with a strong background in data science, and experience in working with imaging data.
Within physical-chemical analytics (PCA) in late phase biologics development, all Novartis new biological entities (NBEs) are supported from proof-of-concept in human (i.e. finalization of the first phase I clinical trial) to commercialization and up to life-cycle management activities. PCA applies a wide range of physico-chemical analytical techniques to characterize the biopharmaceutical products with regards to their purity, identity, and structural integrity. The PCA team is an integral part of the Analytical Development and Characterization unit, which is part of Global Biopharmaceutical Product and Process Development (BPD). The successful applicant will be part of a team in PCA dealing with the characterization of sub-visible particulate matter in protein containing solutions and is expected to work in close interaction with experts in the Bioprocess development community as well as statisticians and data scientists in a global research informatics community (corporate wise). The core task of this position is to develop and support the implementation of a prototype solution of a challenge related to imaging data of sub-visible particles, and implementation into routine application. The prototype solution would preferably be delivered in a user-friendly format for non-expert associates (e.g. shiny applications). More specifically, the position holder is expected to: • have clear understanding on the business context of the development task through diverse channels and stake holders • have full grasp on the current candidate models discussed in the literature, further improve, perform independent literature research and ideally develop other suitable models • generate imaging data of sub-visible particles in the laboratory independently or with minimum assistance • critical assess the performance of candidate models with representative datasets • document the solution(s) in technical reports and scientific papers, outline risks (e.g. due to assumptions and data pre-processing) and design a roadmap of future work if possible • deploy the optimal model as the final solution in a user-friendly format To succeed in this role, the position-holder needs in-depth knowledge in statistical modeling and various machine learning techniques, strong programming skill, collaborative spirit and excellent communication skills. • We offer exciting opportunities to • research on innovative machine learning and statistical application on imaging data in a real business context, with the potential to result in a publication in a peer-reviewed journal with high impact factor • work in a collaborative and interdisciplinary team • gain insights on technical and business practices from one of the biggest pharmaceutical companies
Minimum requirements• PhD in computational biology/chemistry, bioinformatics, (bio)statistics, computer sciences, or related subjects with specialization on computational and/or statistical approaches • Strong programming skills for advanced data analytics, fluent in R or Python is a must, affinity to SQL is desirable • Solid understanding of statistical/probabilistic concepts and various machine learning technologies, hands-on experience with (deep) neural networks is highly desirable • Past working experience with imaging data and specialized software (e.g. fiji) are desirable • Self-motivated team player with excellent communication skills to interact with counterparts with and without in-depth knowledge of statistics and machine learning • Proven track record in scientific publications is desirable • Interest in learning analytical sciences of biophysics and biology
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