Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow
At the Janssen Pharmaceutical Companies of Johnson & Johnson, we are working to create a world without disease. Transforming lives by finding new and better ways to prevent, intercept, treat and cure disease inspires us. We bring together the best minds and pursue the most promising science. We are Janssen. We collaborate with the world for the health of everyone in it. Learn more at www.janssen.com and follow us @JanssenGlobal. Janssen Research & Development, LLC is part of the Janssen Pharmaceutical Companies.
Within Nonclinical Safety, we aspire for translational, world class laboratory and data sciences capabilities focused on patient safety. We want to expand and deliver predictive methods, with translational power, to ensure patient safety during drug treatment and to reduce clinical adverse drug reactions (ADRs). This requires understanding the disease and toxicity mechanisms of prescribed drugs with known toxicity or reported adverse events for developing in vitro screening assays to test drug candidates early in the discovery process and to predict the unintended (toxicity) consequences of drug treatment.
Partial successful efforts in this context are early generation AI/ML chemical structure-based models for predicting adverse drug reactions and toxicity, based on the increasing access to reports on adverse reactions to medicines in large, structured machine-readable formats such as spontaneous adverse event reporting systems and real-world evidence data; which provide the opportunity to perform big data mining and analytics, suitable for predictive modelling approaches.
Emerging new types of information, besides chemical descriptors, are high dimensional cellular image-based data and omics. The combination of a single cellular assay with a highly multiplexed readout can document a broad spectrum of biological activities, including toxicity. Recent advancements in AI and ML- based analyses of high content imaging and omics offer the potential to distinguish drug-induced cellular phenotypes reduced to a multidimensional profile. These profiles can be mined for relevant patterns, revealing unexpected biological activity of drug treatmen
Our aim is to interrogate these multidimensional profiles across drugs with specific known ADRs to identify subgroups or modes of adverse drug reactions; linking to specific shared biological activities and translating them into new throughput in vitro assays for detecting adverse drug reactions early.
Within this context, Nonclinical safety and High Dimensional Biology are recruiting a postdoctoral fellow in data sciences. The post-doctoral fellow will do world-class research in linking cell behaviors to ADRs. The position will be opened on the Beerse campus, which is the flagship R&D center for small molecules within Janssen, investing over 1 billion euros each year in R&D.
Major Duties & Responsibilities
The major task will be data exploration by establishing correlations and building predictive models leveraging state of the art data science and machine learning approaches; segmented in the following activities:
Required Minimum Education: PhD in quantitative sciences (e.g. applied data sciences, (bio)statistics or chemo informatics) or similar
Required Knowledge, Skills and Abilities:
Preferred Knowledge, Skills and Abilities:
Preferred Area of Study: Applied data sciences and biostatistics
Johnson & Johnson (J&J) is an American multinational corporation founded in 1886 that develops medical devices, pharmaceuticals, and consumer packaged goods. Its common stock is a component of the Dow Jones Industrial Average and the company is ranked No. 36 on the 2021 Fortune 500 list of the largest United States corporations by total revenue.
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