Job Description

As a Professor at International Center for Education and Research (ICER), VIT Bangalore, you play a key role in academic instruction, curriculum development, research project guidance and student mentorship. Your expertise in Database Management Systems, Web Application Development, Machine Learning, Data Mining, Deep Learning, Big Data Analytics, Probability and Statistics, and R Programming contributes to fostering an innovative and research-driven learning environment. You are also instrumental in guiding students in the 1+1 masters overseas program, helping them prepare for international academic opportunities. Key Responsibilities: Teaching & Curriculum Development Deliver lectures and hands-on sessions for Probability and Statistics, Database Management Systems, Machine Learning, Data Mining, Deep Learning , Big Data Analytics, and R Programming , incorporating Minitab, MYSQL, scikit-learn, TensorFlow, Hadoop, and PySpark . Design, update, and refine course syllabi to align with industry trends, research advancements, and partner university requirement. Develop and evaluate assignments, projects, and examinations for postgraduate students. Research Innovation Lead and collaborate on research projects with a focus on Artificial Intelligence, Data Science and Business Analytics Guide research projects and mentor Post Graduate Programme student Academic Leadership & Student Mentorship Serve as a mentor for students in the 1+1 masters overseas program , guiding them on research, coursework, and study-abroad applications . Provide Guidance and Exposure to students aspiring for higher education and research roles. Develop innovative assessment strategies that encourage critical thinking and problem-solving. Skills & Tools: Programming & Software Development: Back-end Development: Node.js, Express.js, PHP, Django, Flask Front-end Development: HTML, CSS, JavaScript, React.js, Bootstrap, Tailwind CSS Databases: MySQL, PostgreSQL, MongoDB, Firebase Cloud & Deployment: AWS, Google Cloud, Docker, Kubernetes Data Science & AI: Explainable AI, Deep Learning, Computer Vision, Ensemble Learning Python (scikit-learn, TensorFlow, PyTorch), R (ggplot, dplyr) Data visualization libraries (Matplotlib, Seaborn, D3.js) Big Data & Statistical Analysis: Hadoop, PySpark, Regression Modeling, Hypothesis Testing, Bayesian Statistics Minitab, SQL query optimization, data pipeline development Statistical Analysis: Minitab, Bayesian Statistics, Regression Modeling, Hypothesis Testing. Teaching & Mentorship: Curriculum design, research supervision, collaboration.