RSS feed source: USGS Earthquake Hazards Program
Time2025-07-11 11:32:17 UTC2025-07-11 11:32:17 UTC at epicenterLocation51.574°N 176.672°WDepth52.98 km (32.92 mi)
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Author: WeWorldMedia-admin
RSS feed source: USGS Earthquake Hazards Program
Every day, billions of people trust digital systems to run everything from communication to commerce to critical infrastructure. But the global early warning system that alerts security teams to dangerous software flaws is showing critical gaps in coverage—and most users have no idea their digital lives are likely becoming more vulnerable.
Over the past eighteen months, two pillars of global cybersecurity have flirted with apparent collapse. In February 2024, the US-backed National Vulnerability Database (NVD)—relied on globally for its free analysis of security threats—abruptly stopped publishing new entries, citing a cryptic “change in interagency support.” Then, in April of this year, the Common Vulnerabilities and Exposures (CVE) program, the fundamental numbering system for tracking software flaws, seemed at similar risk: A leaked letter warned of an imminent contract expiration.
Cybersecurity practitioners have since flooded Discord channels and LinkedIn feeds with emergency posts and memes
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RSS feed source: USGS Earthquake Hazards Program
Research Opportunities
Engineering
Work description
• Contribute to the identification of key gaps in the organisation of physical assets and laboratory testing platforms within the x-Energy laboratory.
• Assist in identifying processes for organising physical assets and laboratory testing platforms that are tailored to the specific needs of the x-Energy laboratory.
• Support the implementation of a management platform based on commercial or open-source software (such as ERPNext or Odoo Community), along with maintenance plans for the equipment and infrastructure of the x-Energy laboratory.
• Participate in internal training activities focused on best practices in laboratory management and the utilisation of adopted digital tools.
Academic Qualifications
Be enrolled in a higher education course in Management, Industrial Engineering, Electrical Engineering, or related fields;
Minimum profile required
• Ability to use basic computer tools (spreadsheets, documents, web systems).
• Communication and organizational skills.
Preference
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RSS feed source: USGS Earthquake Hazards Program
Job ID: 259622
INESC TEC | Research Grant (AE2025-0261)
INESC TEC
Research Opportunities
Computer Science
Work description
Development of model/process chains that enable AI-based assistants to support human operators’ decisions in power systems under model risk and uncertainty, and considering joint human-AI learning. Develop methodologies to assess the robustness and safety of human decisions assisted by AI, hybrid co-learning between AI and humans, and fully autonomous AI, considering risk assessment aligned with the EU AI Act, as well as reliability and robustness quantified through the provision of guidelines on how to create and use “adversarial” datasets. Validate the developed methodologies using real data and simulators. Dissemination of the work in national and/or international journals and conferences.
Academic Qualifications
Degree in Computer Science, Informatics of similar area
Minimum profile
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