Mentric Training and Consulting Pvt.Ltd
Website:
mentrictraining.com
Company:
https://www.linkedin.com/company/mentrictraining
Seniority: Mid-Senior level
Industries: Professional Training and Coaching
Job details:
Employment Type: Full-Time
Reporting To: Head of Department / Chief Academic Officer
1. Position Purpose
The Assistant Professor – AI, Robotics & IIoT will contribute to the academic and technical delivery of the B.Tech programme in Artificial Intelligence, Robotics and Industrial Internet of Things (IIoT).
The role is designed for an academically strong and technically hands-on faculty member who can translate concepts in AI/ML, computer vision, robotics, industrial automation, IIoT and digital technologies into practical laboratory learning and industry-oriented student projects.
The candidate will be expected to combine classroom teaching, laboratory delivery, student mentoring, curriculum development and applied research, with a strong focus on developing students' practical engineering capabilitie.
2. Educational Qualification & Eligibility
- M.E./M.Tech. in Artificial Intelligence, Computer Science & Engineering, Electronics, Electrical, Instrumentation, Mechatronics, Robotics or a closely allied engineering discipline.
- First Class or equivalent in Bachelor's or Master's degree.
- Relevant teaching, research, industrial or laboratory experience will be preferred.
- Candidates with strong hands-on industry exposure in AI, automation, robotics or IIoT are encouraged to apply.
- Relevant research publications in Scopus/SCI/UGC-CARE indexed journals will be an advantage.
3. Technical Competencies
The candidate should have working knowledge and practical exposure to several of the following areas:
Artificial Intelligence & Machine Learning
- Supervised and unsupervised learning.
- Machine learning model development, training and evaluation.
- Deep learning and neural networks.
- CNNs, RNNs and introductory Transformer architectures.
- Python, TensorFlow/PyTorch and scikit-learn.
- Application of AI/ML to industrial and manufacturing problems.
Computer & Machine Vision
- Image acquisition and preprocessing.
- Object detection and image classification.
- Defect detection and dimensional inspection.
- Camera calibration.
- Industrial machine vision applications.
Robotics
- Fundamentals of robot kinematics and trajectory planning.
- Forward and inverse kinematics.
- Robot programming.
- ROS/ROS2 fundamentals.
- Industrial robots and collaborative robots.
- Exposure to FANUC or equivalent industrial robots will be an advantage.
Industrial Automation
- PLC programming and Ladder Logic.
- HMI and SCADA fundamentals.
- Sensors, actuators and transducers.
- Pneumatics and electro-pneumatics.
- Industrial automation platforms, preferably SMC/Schneider Electric or equivalent.
IIoT & Edge Computing
- Industrial IoT architecture.
- Edge computing and edge inference.
- Industrial communication protocols such as Modbus, Profinet, OPC-UA and MQTT.
- Data acquisition and time-series data.
- Industrial gateways and connected systems.
Digital Twin & Simulation
- Fundamentals of digital twins.
- Process simulation and virtual commissioning.
- Industrial system modelling.
- What-if and scenario analysis.
Predictive Maintenance
- Condition monitoring.
- Vibration and temperature-based monitoring.
- Basic predictive maintenance models.
- Remaining Useful Life concepts.
- AI applications in maintenance.
4. Key Responsibilities
A. Teaching & Academic Delivery
- Deliver undergraduate courses in AI, Machine Learning, Robotics, IIoT, Automation and related engineering subjects.
- Prepare lesson plans, presentations, assignments, question banks and assessment materials.
- Deliver both theoretical and practical sessions effectively.
- Ensure alignment of teaching activities with prescribed curriculum and learning outcomes.
- Support course mapping and CO–PO attainment activities.
- Incorporate industry case studies, real-world examples and practical demonstrations into teaching.
- Support curriculum development and periodic updating of course content.
B. Laboratory & Practical Training
- Conduct hands-on laboratory sessions in AI, machine learning, robotics, automation and IIoT.
- Support operation and utilisation of the AIT-400 AI Machine Lab and related robotics/automation facilities.
- Prepare and maintain laboratory experiment sheets, manuals and practical assessments.
- Demonstrate AI-enabled industrial applications and automation workflows.
- Support equipment commissioning, calibration and basic troubleshooting under the guidance of senior faculty/technical teams.
- Maintain laboratory records and ensure proper adherence to safety procedures.
- Participate in relevant OEM technical training and certification programmes.
C. Research & Innovation
- Participate in applied research activities in AI, robotics, automation and IIoT.
- Develop research ideas and contribute to research papers, conference papers and journal publications.
- Support faculty-led funded research and consultancy projects.
- Identify industry-oriented problems that can be converted into student projects or research activities.
- Support development of prototypes, proof-of-concepts, patents and innovative solutions.
- Guide students in research methodology and technical project development.
D. Student Project & Mentoring
- Guide B.Tech students in mini-projects, major projects and technical assignments.
- Encourage students to work on real-world industrial problems.
- Mentor students in AI, robotics, automation and IIoT applications.
- Support student participation in hackathons, technical competitions, workshops and certification programmes.
- Assist students in developing technical portfolios and industry-ready project skills.
- Track student academic and technical progress and provide appropriate mentoring.
E. Industry & Professional Engagement
- Participate in technical workshops, seminars, guest lectures and industry interaction programmes.
- Support industry-sponsored projects and live problem statements.
- Assist in coordinating internships, industrial visits and technical training programmes.
- Work with OEM and industry partners for practical learning initiatives.
- Stay updated with emerging technologies and industrial trends in AI, robotics and automation.
5. Preferred Candidate Profile
The ideal candidate should be:
- Passionate about applied AI, robotics and industrial automation.
- Comfortable conducting hands-on laboratory sessions.
- Able to connect theoretical concepts with real-world industrial applications.
- Strong in Python and AI/ML fundamentals.
- Interested in industrial robotics, PLC, IIoT and machine vision.
- Capable of mentoring students on technical projects.
- Willing to learn and work on platforms such as SMC AIT-400, Schneider Electric and industrial robotics systems.
- Research-oriented with an interest in publishing applied research.
- Comfortable working in a multidisciplinary academic and industry environment.
6. Role Expectations
The Assistant Professor is expected to contribute to building an industry-aligned learning environment where students gain both theoretical understanding and practical engineering competence.
The successful candidate should demonstrate the ability to move beyond classroom teaching and actively participate in laboratory implementation, industrial projects, student innovation, applied research and technology-driven academic activities.
Hands-on exposure to industrial equipment, automation systems, robotics platforms or AI-enabled manufacturing applications will be highly valued.
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