Building of machine learning models for agri-genomic trait predictions and development of a digital Agri-Tech platform Development of digital and analytical models on agri data ecosystems to support the development and delivery of timely, targeted information and services to make farming profitable and sustainable, while delivering business objectives Data analytics and data driven modelling for chemical and biological systems for RD objectives across various areas such as material sciences, nutritional sciences Creating a visualizer and dash boards to summarize data analytics outcomes for stakeholders Supporting the in-house projects with data analytics QUALIFICATIONS AND EDUCATION REQUIREMENTS : Qualifications BE/BTECH/M.Sc. in Computational Applications (MCA), Statistics, Bioinformatics or any relevant field with 2+yrs of relevant experience. Experience Advanced data modelling/machine learning, analytics and statistical assessment for complex data such as genomics, chemical reaction systems Exposure to biological systems (eg. microbiome/agri-genomics) and working on cloud systems (Azure, AWS or Google-Cloud etc.) is an added advantage Skills Required A successful candidate should be well versed with statistical tools relevant for biological system (eg bio-conductor) Must have a strong background in data analytics and machine learning Knowledge of Python is required Should have good command in R
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