Shiftwork scheduling is a critical task in workforce management, particularly in industries requiring continuous operations, such as healthcare, manufacturing, and emergency services. Traditional scheduling approaches mainly focus on balancing workload, minimizing labor and basic fatigue conditions to increase productivity. However, these methods frequently neglect the physiological and cognitive effects of shiftwork on employees, particularly those related to disruptions in the circadian cycle; this governs sleep-wake patterns, cognitive performance, and overall well-being. Shiftwork, especially night shifts and rotating schedules, can significantly disrupt this cycle, leading to fatigue, decreased productivity, increased error rates, and long-term health issues like cardiovascular diseases and metabolic disorders. Therefore, it is imperative to integrate circadian cycle considerations into shift scheduling models to enhance worker well-being and performance while maintaining operational efficiency. Thus, this study proposes a MILP model for the multi-skill shiftwork scheduling problem, explicitly accounting for circadian cycle effects; in particular, circadian-based fatigue and recovery constraints, operational constraints such as labor regulations, demand coverage, and shift continuity. The objective function penalizes excessive consecutive shifts and lack of rest to minimize adverse effects of shift rotations and night shifts. A set of random instances was generated to evaluate model performance and results demonstrate its capability to produce schedules that improve worker well-being while maintaining high operational efficiency. Computational results show that incorporating circadian cycle considerations leads to more sustainable schedules with reduced fatigue-related productivity losses. The findings highlight the importance of integrating human-centric factors into workforce scheduling and provide a foundation for future research in circadian-aware scheduling methodologies.