Senior Researcher, Civil Safety Sciences

Darum lohnt es sich

Strong candidates may come from any of, or combinations across: biosecurity, microbiology, ecology, environmental or atmospheric science, agricultural and food systems science, chemistry, materials science, physics, public health, biomedical or systems engineering, resilience engineering, security sciences, or related fields Substantive familiarity with adversarial environments and adversarial reasoning, broadly construed: grounded in security studies, biosecurity, cybersecurity, defense analysis, red‑team ing, safety engineering, dual-use technology assessment, or comparable experience reasoning rigorously about deliberate misuse and worst-case dynamics Demonstrated ability to reason carefully about hazards that lack robust historical data or settled detection paradigms 5+ years of relevant research or applied experience, with a track record of running independent projects from framing through delivery Strong publication record or equivalent body of work on technological risk, resilience, detection science, or related domains Excellent written and verbal communication, with proven ability to translate technical content for policymakers, funders, and non-specialist audiences Systems thinking and comfort with substantial uncertainty and rapidly shifting knowledge landscapes Substantive grounding in modern AI capabilities and trajectories, sufficient to anticipate how advancing AI reshapes threat and defense landscapes in your areas of work Self‑directed, with sound judgment for identifying high‑leverage problems under broad rather than micromanaged direction Hard Skills AI-enabled hazard analysis dynamic pathogen surveillance deep resilience engineering biosphere-scale vulnerability analysis scientific metaresearch adversarial reasoning risk assessment detection science systems engineering environmental toxicology Soft Skills written communication verbal communication systems thinking self-directed sound judgment collaboration project management analytical thinking decision support cross-border coordination Certifications & Qualifications PhD MS #J-18808-Ljbffr Conduct structured horizon-scanning for novel AI-enabled hazard classes, and develop methodologies for reasoning rigorously about threats that lack historical base rates or established scientific communities Investigate next-generation detection sciences, such as dynamic and adaptive pathogen surveillance, and analogous open-ended approaches for other emerging hazard modalities Pursue feasibility analyses on deep resilience and lifeline capacities engineered to function when conventional infrastructure, sunlight, or centralized coordination cannot be assumed Analyze biosphere-scale vulnerabilities, including geoengineering, synthetic microbes for terraforming or remediation, and nontraditional environmental toxicology arising from AI-enabled activity Identify and selectively advance defensive, stabilizing, and transparency-enhancing technologies whose differential acceleration favors humanity Develop scientific metaresearch on how evidence is generated, aggregated, and translated into action where conventional empirical feedback loops are weak Build scientific coordination capacity through standards, convenings, and cross-border working relationships, and equip frontline responders and community networks with usable decision support Co-author grant applications, build analytical tools that make catastrophic risks more legible, and translate findings for policymakers, technical audiences, and the public Collaborate across CARMA programs to integrate civil safety perspectives with broader risk assessment, governance, and technical safety workstreams Requirements Advanced degree (PhD or >1 MS preferred) in a hard-science or engineering discipline, with demonstrated breadth across multiple natural science fields.