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Trust is earned. In research AI, it comes from transparency, traceability, and strong data protection. LeapSpace™ is Elsevier’s research-grade AI workspace built on trusted science. It is designed with transparency and clear trust markers, plus enterprise-grade privacy and security, so insights are explainable and traceable. Try LeapSpace today: http://spkl.io/604776SSV
Elsevier has been ranked #1 on Comparably’s Best Product & Design Teams 2026 list. Our teams are building products that shape how the world’s researchers, clinicians, and scientists discover, use, and share knowledge. That takes craft, vision, and people who genuinely care about what they make. This recognition belongs to every designer, product manager, researcher, and engineer who shows up for purposeful work every day. If you want to do the best work of your career, and work that matters, we’d love for you to join us. 👉 We’re hiring: http://spkl.io/60447DLmn | 🏆 Award information: http://spkl.io/60457DLmX
Responsible AI starts with trusted content. Elsevier collaborates with publishers, societies, and data providers to help ensure our research and clinical-grade AI solutions are grounded in high-quality scientific and medical knowledge. Read more on how we approach content coverage, attribution, transparency, privacy and IP protection, as AI changes how researchers and clinicians discover and use high-quality information: http://spkl.io/60407Dmv0
Fast answers built on a shallow evidence base do not solve the bias problem. They reproduce it faster. As AI becomes part of research and decision-making, the quality of the underlying evidence matters as much as the capability of the model. Better decisions require broader evidence, trusted sources, and insights that can be traced back to where they came from. Read more: http://spkl.io/60447D6DY
We’re growing our Data Science teams at Elsevier (RELX). These roles sit at the intersection of data, machine learning, and real-world impact—helping researchers, clinicians, and organizations solve meaningful global challenges. You’ll work on everything from advanced analytics and ML models to scalable data platforms that power decision-making in science and healthcare. Hiring across levels (Data Scientist → Manager) and locations (US, UK, NL). Take a look: https://bit.ly/3SaLXvj
Purposeful work, continuous growth, and colleagues who care are at the heart of the Elsevier Experience. HRGrapevine takes a closer look: https://bit.ly/3QNpBPY Join us: https://bit.ly/4cZeNH7
The future we build could depend on research we don’t read. Basil Mahfouz's work highlights a striking gap: roughly two-thirds of science flagged as highly relevant to policy is never cited. Not because it is weak, but because it is invisible. As AI changes how evidence is discovered and used, the question is not only whether it can summarize research. It is whether it can help widen the field of view. Read more: http://spkl.io/60487D6BO
Elsevier has launched an Ebola Information Center to support the global response to the Bundibugyo virus outbreak in the Democratic Republic of Congo and Uganda. The center provides healthcare professionals, researchers, policymakers and the public with free access to clinical guidance, peer-reviewed research, early-stage findings, datasets and AI-assisted research tools. Resources include the Ebola Healthcare Hub, ScienceDirect research content, The Lancet and Cell Press Ebola collections, the SSRN Ebola Hub, Mendeley Data, and access to LeapSpace, with new content added as evidence emerges. Learn more: http://spkl.io/60437DkhD
Elsevier is hiring across Engineering & Technology—from software and data to AI and platform roles. These teams build the systems that help advance science and improve health outcomes globally. If you know engineers who want their work to matter (and enjoy solving complex problems at scale), this is a great opportunity to explore. 🔗 View open roles: https://bit.ly/4sEdvFM
Modern medicine can shift the gut microbiome within months. New research in Elsevier's Cell Reports by Cell Press found that after only limited medical contact, the gut microbiota of remote Amazonian Indigenous communities began shifting toward patterns more common in industrialized populations, even without major diet or lifestyle change. Over four months, microbial diversity declined, fiber-associated bacteria decreased, and genes linked to antimicrobial resistance became more common. The strongest shifts were seen in children. Read more. 👇
