Minera Frisco, UAZ Partner to Empower Mining Professionals
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Minera Frisco, UAZ Partner to Empower Mining Professionals

Photo by:   Shahadat Rahman
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Paloma Duran By Paloma Duran | Journalist and Industry Analyst - Thu, 10/03/2024 - 10:47

Minera Frisco and the Universidad Autónoma de Zacatecas (UAZ) have established a collaboration agreement to promote education, research, and innovation in the mining sector. This partnership aims to strengthen the relationship between the mining industry and academia, offering students professional opportunities.

The agreement aims to establish internship and practical training programs at Minera Frisco, allowing UAZ students to acquire hands-on experience in mining operations. It also encourages their participation in research projects designed to leverage innovation in addressing industry challenges. "The collaboration between the company and the university generates knowledge that benefits both institutions and drives progress across the entire region," says Alfonso López, Metallurgical Research Manager, FID.

Luis Eduardo Ramírez, General Director of Operations, Minera Frisco, says that the company is committed to fostering educational and economic transformation in Zacatecas. "Mining serves as a vital engine of development for our community, and through this agreement, we aspire to cultivate the leaders who will shape the future of the sector," Ramírez says.

Many mining companies are allying with universities to enhance students' capabilities and foster their integration into the sector. In August, Tecnológico de Monterrey inaugurated Mexico's first Mining Digitization Academy for Women at the Santa Fe campus. Driven by Women in Mining (WIM) Mexico and INNOMOTICS, the academy gathered 70 women from mining companies such as Peñoles, Grupo México, and Newmont. Over the course of eight weekly sessions, participants explored key topics relevant to the digital transformation of the sector, including digital twins, critical asset monitoring, cybersecurity, digital leadership, and machine learning.

Photo by:   Shahadat Rahman

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