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A leading logistics consulting firm in Hamburg is seeking a Bachelor’s or Master’s student to support their research team. The role involves working on application-oriented studies in supply chain management, data preparation, and analysis using Python. Strong candidates will have solid programming skills and an interest in logistics-related scientific work.
Our 4flow research team conducts exciting research projects, develops innovative digitalization solutions and creates market-relevant studies in the field of supply chain management and logistics.
Support us full-time as a Bachelor’s or Master’s student as part of your thesis project!
Reducing inventory can lead to significant cost savings. However, to ensure delivery reliability in volatile environments, inventory is essential at various stages of the supply chain. This topic focuses on developing and enhancing methods for holistic inventory optimization, considering uncertain lead and replenishment times. The goal is to ensure practical applicability by integrating diverse industry-specific characteristics.
Lack of visibility beyond Tier-1 suppliers makes inbound supply chains vulnerable to unforeseen risks and delays proactive action. This topic aims to develop an innovative ML / GenAI framework that automatically predicts geographic waypoints and transport modes, enabling data-driven insights to support inbound logistics management.
Limited transparency regarding logistics hubs used within supply chain routes leads to delayed risk detection and missed optimization opportunities. This topic involves developing an ML / GenAI framework that automatically predicts transshipment points and connections based on known origin-destination pairs, strengthening logistics planning through data-driven decision support.