Job
Description
Woxsen University is a premier institution at the forefront of technology and business education in India. Strategically located in Hyderabad's innovation corridor, we bridge academic excellence with industry relevance through cutting-edge programs and research initiatives. Our research-intensive faculty drive intellectual leadership that shapes academic discourse and advances the frontiers of computational sciences, artificial intelligence, and machine learning. Available Positions We are currently seeking research-focused professors specializing in the following disciplines: Computer Science & Engineering Artificial Intelligence Machine Learning Data Science Computational Systems Position Overview We seek accomplished research scholars with exceptional capabilities in investigating computational systems, algorithmic approaches, and intelligent technologies. The ideal candidates will demonstrate research excellence through publications in top-tier journals and conferences, and possess the ability to develop innovative research programs that advance the theoretical foundations and practical applications of computational sciences. These positions require individuals who can build significant research portfolios, mentor junior scholars, and lead interdisciplinary initiatives examining the mathematical, computational, and engineering dimensions of intelligent systems. Key Responsibilities Research & Scholarly Impact (70%) Maintain a rigorous research agenda resulting in publications in premier conferences and journals (NeurIPS, ICML, ICLR, CVPR, ICCV, ACL, AAAI, IJCAI, KDD, JMLR, TPAMI, TNNLS, etc.) Secure competitive research grants from national and international funding bodies (DST, SERB, MeitY, NSF, EU Horizon, industry research labs) Develop innovative algorithmic approaches, computational models, and system architectures Lead a research group focused on specific areas of computational sciences and AI/ML Design and implement cross-disciplinary research initiatives bridging computational approaches with domain applications Contribute to global research networks and collaborative projects with international scholars Apply the GTRMP framework with primary emphasis on research excellence and theoretical advancement Present research at prestigious academic conferences and research symposia Serve on program committees and editorial boards of leading conferences and journals Teaching & Student Development (20%) Teach advanced courses in computational sciences, AI/ML foundations, and specialized topics Supervise doctoral students and mentor early-career researchers in computational methods Develop research-informed curriculum for graduate programs in CS/AI/ML Create opportunities for student involvement in high-quality research projects Design specialized research seminars and workshops for doctoral students Foster interdisciplinary thinking and methodological rigor in student research Guide students in preparing submissions for top-tier conferences and journals Institutional Development & External Relations (10%) Contribute to departmental and university research governance Participate in faculty recruitment and development initiatives Support research accreditation and quality enhancement efforts Collaborate with colleagues on interdisciplinary computational research initiatives Enhance Woxsen's reputation as a center of excellence for computational sciences and AI research Develop relationships with external research institutions, industry research labs, and funding agencies Contribute to open-source software development and research infrastructure when appropriate Qualifications Essential PhD in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or related discipline from a globally recognized research institution Outstanding research profile with multiple publications in top-tier conferences and journals in computational sciences, AI, and ML Demonstrated success in securing competitive research grants Strong theoretical foundations and methodological expertise in computational and algorithmic approaches Evidence of research impact through citations, h-index, and scholarly recognition Experience in doctoral supervision and mentoring early-career researchers Excellent communication skills with ability to disseminate complex computational research to diverse audiences Active participation in international research networks and scholarly communities Desirable H-index of 20+ with a strong citation record Track record of publications at premier venues (NeurIPS, ICML, ICLR, CVPR, ACL, etc.) Experience leading funded research projects and managing research teams Contributions to open-source software, datasets, or research infrastructure Track record of successful research collaborations across institutions and disciplines Experience organizing workshops at major conferences or serving as area chair Demonstrated ability to bridge theoretical advances with computational implementations Experience with innovative methodological approaches and interdisciplinary applications Editorial or program committee experience with respected conferences and journals Record of successful PhD placement at research-intensive institutions Industry research experience at leading AI/ML labs (optional) Discipline-Specific Research Focus Areas Computer Science & Engineering Algorithm design and computational complexity High-performance computing and distributed systems Computer architecture and hardware-software co-design Programming languages and software engineering Security, privacy, and cryptographic systems Human-computer interaction and user experience Systems for AI/ML and computational infrastructure Artificial Intelligence Knowledge representation and reasoning Planning and decision-making under uncertainty Multi-agent systems and game-theoretic approaches AI for social good and ethical AI development Cognitive architectures and artificial general intelligence Human-AI collaboration and interactive AI systems Verification, validation, and safety of AI systems Machine Learning Deep learning architectures and optimization Reinforcement learning and sequential decision making Probabilistic models and Bayesian inference Unsupervised, self-supervised, and representation learning Transfer learning, meta-learning, and few-shot learning Fairness, accountability, transparency, and ethics in ML Theoretical foundations of machine learning Data Science Large-scale data processing and analytics Causal inference and experimental design Time series analysis and forecasting Network science and graph analytics Natural language processing and text mining Computer vision and multimedia analytics Scientific data analysis and computational statistics Computational Systems Embedded systems and IoT architectures Autonomous systems and robotics Cyber-physical systems and control theory Quantum computing and quantum information systems Computational biology and bioinformatics Computational sustainability and smart infrastructure Edge computing and mobile systems Show more Show less
