Postdoc Multiscale Sensing and AI for Tailings Storage Facility Monitoring

Postdoc Multiscale Sensing and AI for Tailings Storage Facility Monitoring

Job description

Looking for an impactful Postdoc opportunity in sustainable development?

The global transition toward a low-carbon economy has triggered a sharp increase in the demand for critical minerals. This surge places mounting pressure on the mining sector to not only scale up production but to do so in a socially and environmentally responsible manner. Tailings storage facilities (TSFs), which store the byproducts of mining processes, pose significant environmental and safety risks when inadequately monitored or managed. Catastrophic TSF failures can lead to irreversible ecological damage, loss of life, and erosion of public trust in the mining industry.

Despite growing regulatory and societal expectations, current TSF monitoring practices often lack the spatial and temporal resolution needed to provide early warnings or to comprehensively assess facility performance over time. Multiscale sensor technologies including satellite remote sensing, UAV-based systems, ground-based instrumentation, and in-situ monitoring, offer a transformative opportunity to establish continuous, predictive, and integrated surveillance systems for tailings facilities.

An international consortium, including TU Delft, is collaborating on the GAIA-TSF (Geospatial Artificial Intelligence Analysis for Tailings Storage Facilities) project to design and develop a prototype system for the automated detection of anomalies and risks in TSFs. This system utilize sensor-derived data and machine learning algorithms to enable continuous, multi-scale, and multi-level monitoring and characterization of TSFs. 

Are you passionate about advancing AI-driven solutions for the sustainable and safe management of mining waste?

This postdoctoral research position offers the opportunity to actively contribute to this interdisciplinary project alongside multiple academic, industry, and governmental partners. The selected candidate will help address the pressing need for advanced sensing and monitoring frameworks by developing data fusion techniques, identifying key structural and environmental indicators, and supporting the creation of next-generation decision-support tools. These efforts are critical for improving the safety, sustainability, and environmental accountability of mineral resource development.

Job requirements

You hold a PhD in a relevant field such as geoinformatics, resource engineering, environmental engineering, geospatial science, computer science, artificial intelligence, or data science.

We also welcome applicants from geoscience or environmental science backgrounds, particularly those with strong expertise in advanced data analytics.

You also bring:

• Proven experience working with sensor-derived data
• Strong expertise in machine learning, geostatistics, and data fusion techniques, with a focus on spatial and time series data analytics.
• Familiarity with environmental management and monitoring challenges
• Excellent conceptual thinking and analytical problem-solving abilities
• Effective communication skills
• Proficiency in relevant software tools and programming languages, such as Python or R
• Strong interpersonal and teamwork skills

Does this position spark your interest?

Even if you don’t meet every requirement, but have a strong background and passion in some of the listed areas, we’d still love to hear from you!

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty of Civil Engineering and Geosciences

The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource availability, urbanisation and clean water. Our research projects are conducted in close cooperation with a wide range of research institutions. CEG is convinced of the importance of open science and supports its scientists in integrating open science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.

Conditions of employment

• Duration of contract is 1 year.
• A job of 36-38 hours per week.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Additional information

For more information about this vacancy, please contact dr. F.S. Desta, e-mail: F.S.Desta@tudelft.nl. 

To get an idea of the projects that our section was and is involved in:

https://trim4postmining.com/

https://eitrawmaterials.eu/project/insite/

https://cordis.europa.eu/project/id/641989