Job Overview
We are seeking an visionary Lecturer and Researcher in Intelligent Logistics Systems to join our faculty. We are looking for talented engineers who can fuse advanced operational research with modern AI to solve the complex supply chain challenges of the future. You will prepare the next generation of logistics engineers to move beyond traditional manual operations and into an era of autonomous, self-optimizing, and resilient supply chains.

Job Responsibilities
Instructional Delivery: Lead courses such as Intelligent Supply Chain Systems, Data-Driven Logistics, Predictive Analytics, Warehouse Automation, and Autonomous Transportation Networks.

Curriculum Innovation: Develop a pioneering curriculum that bridges the gap between traditional industrial engineering and "smart" technology, covering areas like digital twins, IoT-enabled tracking, and AI-based optimization.

Research & Scholarship: Lead a research group focused on high-impact areas: multi-agent coordination in logistics, AI-enhanced demand forecasting, resilient supply chain design, or sustainable green-logistics optimization. Secure competitive grants and publish in top-tier journals (e.g., INFORMS, Transportation Science).

Applied Lab Leadership: Manage a "Smart Logistics Lab," where students work with real-world datasets, digital twin simulation platforms, and hardware prototypes like autonomous mobile robots (AMRs) or automated sorting systems.

Mentorship: Supervise Master’s and PhD students, fostering a research environment that values both theoretical rigor and real-world industrial applicability.

Industry Collaboration: Establish strong links with leading logistics, e-commerce, and manufacturing firms to create internship pipelines and collaborative projects that keep the department at the cutting edge.

Departmental Collaboration: Work with faculty in Computer Science and Data Science to foster an interdisciplinary approach to logistics technology.

Job Requirements
Education: PhD in Industrial Engineering, Operations Research, Logistics Engineering, or a closely related field is required.

Experience: Demonstrated excellence in research with a strong publication record. Professional engineering experience in supply chain optimization, logistics technology, or automation is highly valued.

Technical Skills:

Optimization: Strong proficiency in mathematical programming (CPLEX, Gurobi) and meta-heuristics.

Data & AI: Competence in Python or R for data analysis, machine learning libraries (scikit-learn, TensorFlow/PyTorch), and simulation software (AnyLogic, Arena).

System Integration: Knowledge of SCM architectures, including ERP/WMS/TMS systems and their integration with IoT sensors and automated hardware.

Soft Skills:

Systems Thinking: Ability to model complex, dynamic environments and identify high-leverage points for technological intervention.

Translational Ability: Talent for explaining deep technical/mathematical concepts to students and industry partners in a compelling, practical way.

Entrepreneurial Mindset: A proactive approach to research that seeks to solve actual industry pain points through technical innovation.

Collaborative Leadership: Desire to mentor students and lead interdisciplinary research teams effectively.

Benefits
Competitive Compensation: High-tier academic salary package with significant potential for research funding, industrial consulting, and project-based rewards.

Professional Development: Support for publishing in leading journals, attending top global conferences (e.g., IEEE, INFORMS), and maintaining industry connections.

Advanced Facilities: Access to dedicated smart logistics labs, high-performance computing resources for optimization modeling, and industry-standard simulation software suites.

Comprehensive Benefits: Full insurance coverage, academic leave, and retirement benefits in accordance with local labor laws.

Career Growth: Defined pathways to Tenured Associate/Full Professor, Research Group Lead, or Director of Logistics Innovation Centers.

Lecturer in Logistics Engineering, Researcher in Smart Logistics, Supply Chain Tech Faculty, Industrial Engineering Professor, Operations Research Specialist.

Industry Keywords: Smart Logistics, Supply Chain Optimization, Operations Research, Digital Twin, IoT, Predictive Analytics, Warehouse Automation, Autonomous Systems.

Attributes: Analytical, Innovative, Systems-focused, Collaborative, Data-driven, Pragmatic.

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