Egnyte’s Post

Let's discuss self-driving labs from the perspectives of workflows and reproducibility. Self-driving labs are revolutionizing research in biology and chemistry by automating experiments and enabling high-throughput data collection. This automation speeds up the discovery process and enhances the reproducibility of scientific results. By integrating advanced workflows, these labs ensure that every step of the experimental process is documented and easily replicable. Embracing workflows and reproducibility in self-driving labs means embracing a future where scientific discoveries are made faster, more efficiently, and with greater confidence in their accuracy. Ewa Deelman Michela Taufer Global Computing Laboratory CI Compass National Science Foundation (NSF) #PASC24 #PASC25

Join Ari Berman, Ph.D., CEO at BioTeam, Inc., on July 17 for his presentation to the Dell HPC & AI Community: Cutting-Edge or Overhyped? An Insider's View on HPC and AI Trends in Life Sciences. Dr. Berman will explore the most impactful and promising technologies in life sciences, offering a candid, experience-based assessment. Discover how advancements in HPC, storage, data transfer, networks, cloud services, data science, AI, and machine learning are revolutionizing data-intensive science today and shaping its future. Find out which innovations are truly state-of-the-art and which ones fall short of the hype. Register now: https://lnkd.in/ggdYeaHr

If you're an Illinois researcher with a big problem to solve, you need robust resources & support—and #IllinoisComputes is here for you. We're thrilled to announce an additional GPU allocation for Radiant, NCSA’s powerful private cloud computing service dedicated to empowering researchers at the University of Illinois. Join the growing community of researchers leveraging Radiant to unlock new insights & drive innovation. Consistent with Illinois' land grant promise, Illinois Computes is ensuring that every UIUC researcher has access to top-notch computing resources, ensuring inclusivity in scientific inquiry. In fact, Illinois Computes support is available at no charge to researchers across disciplines at Illinois. Curious about how this new Radiant allocation might elevate your research? 🔗 Learn more about this GPU addition: https://lnkd.in/gTR888ii 🔗 Find out how Illinois Computes offers research support at https://lnkd.in/gSmYydJZ 🔗 Request an allocation on Radiant via Illinois Computes at https://lnkd.in/gMvHWCBX

✔️ Reproducibility starts with consistent confluency, essential for minimizing variability in experimental outcomes, including areas like #geneexpression, #proteinproduction, #drugsensitivity, and #cellcycledynamics. 🎬 New Video Alert! Hear from Charlotte, a PhD student at Australia's UNSW, on how Millicell® DCI’s #confluency and #cloud capabilities are transforming research. 💥 Watch here: bit.ly/3VmvfYE Simplify your workflow and achieve reproducible results with Millicell® DCI.

✔️ Reproducibility starts with consistent confluency, essential for minimizing variability in experimental outcomes, including areas like #geneexpression, #proteinproduction, #drugsensitivity, and #cellcycledynamics. 🎬 New Video Alert! Hear from Charlotte, a PhD student at Australia's UNSW, on how Millicell® DCI’s #confluency and #cloud capabilities are transforming research. 💥 Watch here: bit.ly/4fW9szh Simplify your workflow and achieve reproducible results with Millicell® DCI.

The MOC Alliance annual workshop will be held February 28-29, 2024 at the Boston Umiversity George Sherman Union, 774 Commonwealth Ave., Boston, with featured topics including the newly launched AI Alliance, cloud infrastructure for data-intensive workloads, expanding access to resources via the open cloud, systems research, and more. See the full list of presenters below. The MOC Alliance provides a structure for a set of interrelated projects that have grown up around the Mass Open Cloud (MOC) and Massachusetts Green High-Performance Computing Center (MGHPCC). These projects include production cloud services (NERC, NESE, OSN) for domain researchers operated and facilitated by university research IT, a national testbed for cloud research (OCT), projects to enable scientific and medical researchers (Biogrids, ChRiS), and projects to engage the open source (OI labs) and system research (Red Hat Collaboratory, i-Scale) communities. Red Hat is a founding member of the MOC Alliance and co-leads the Red Hat Collaboratory at Boston University partnership. Click below to read more about this workshop on Feb 28-29. Hugh Brock :: Heidi Dempsey :: Chris Wright :: #Research #University https://lnkd.in/g2ANUSDW

Discover how specialised HPC cloud solutions are accelerating breakthroughs in drug discovery, genomics, and biotech, all while cutting costs. 📄 In this insightful White Paper from Viridien, explore: ➡️ How to overcome traditional computing bottlenecks ➡️ Advanced solutions for processing complex data at scale ➡️ The impact of HPC on cutting-edge simulations and research efficiency 🔬 Don't let outdated infrastructure slow down innovation. Learn how cloud-based HPC empowers researchers to achieve faster, cost-effective results. 📥 Download now and stay ahead in the race for discovery: https://lnkd.in/ebkd5KVt #HPC #DrugDiscovery #Genomics #CloudComputing #Innovation

Check out our latest whitepaper to explore how emerging #HPC models are delivering faster, more scalable and cost-effective simulations—outpacing on-premise setups and traditional #cloud access 👇

Hey Everyone! 👋 I’m thrilled to announce that my research article, "𝑭𝑨𝑪𝑻: 𝑨𝒖𝒕𝒐𝒆𝒏𝒄𝒐𝒅𝒆𝒓 𝒂𝒏𝒅 𝑨𝒕𝒕𝒆𝒏𝒕𝒊𝒐𝒏 𝑪𝒐𝒏𝒗-𝑳𝑺𝑻𝑴 𝒃𝒂𝒔𝒆𝒅 𝑪𝒐𝒍𝒍𝒂𝒃𝒐𝒓𝒂𝒕𝒊𝒗𝒆 𝑭𝒓𝒂𝒎𝒆𝒘𝒐𝒓𝒌 𝒇𝒐𝒓 𝑪𝒍𝒐𝒖𝒅 𝑪𝒐𝒗𝒆𝒓 𝑷𝒓𝒆𝒅𝒊𝒄𝒕𝒊𝒐𝒏", has been published in IEEE Access! 📖✨ ☁ ⛅ ⛈ In this work, we introduce FACT, a framework that predicts future cloud cover patterns and formations from satellite image data. By combining autoencoders with attention-based ConvLSTM architecture and post-processing, we achieved a novel solution for both performance and computational efficiency. This research has exciting real-world applications in areas such as agriculture, aviation, and solar industries. 📚 Check it out here: https://lnkd.in/eMZBAB28 I would like to extend my gratitude to my mentors Sudeep Tanwar, Nilesh kumar Jadav and Rajesh Gupta for their constant support throughout the research.

Register now at https://lnkd.in/gunPRvNB The Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES) Initiative aims to modernize the biomedical research ecosystem by reducing economic and process barriers to accessing commercial cloud services.   For STRIDES principal investigators, users, and any bioinformatics professionals interested in reducing the economic barrier of cloud costs, this webinar demonstrates how to use Memory Machine Cloud in AWS to shave 50% or more off cloud costs with Spot instances and checkpoint restore.   Attendees to this webinar will learn about: - Types of pipelines that previously could not run safely on Spot instances. - Typical problems that can be addressed with checkpoint restore. - Memory Machine WaveRider technology that allows workloads to surf compute instances during runtime. - Memory Machine SpotSurfer technology that allow workloads to handle Spot terminations.