This webinar discussed how to integrate Posit Workbench with AWS ParallelCluster so that user IDE and data science web notebook sessions are spawned on ParallelCluster compute fleet nodes.
In this webinar, Dr. Simon Twigger will share best-practice approaches to solving complex technology and data science problems that slow down scientific research using examples drawn from various consulting projects, and provide some tips and tricks that anyone can use to solve similar challenges.
Scientists, scientific leaders, and IT leaders are invited to join founders Stan Gloss, Bill Van Etten, and Chris Dagdigian, together with CEO Ari Berman, for a lively discussion about the importance of scientific data as the foundation of modern scientific discovery.
Join Ari Berman, Ph.D., CEO at BioTeam for his FAIR or Fiction? Data Harmony in Biomedicine webinar on November 9, 1pm EST. Dr. Berman will discuss the drivers of data analytics in biomedicine, where we stand on the journey towards FAIR (Findable, Accessible, Interoperable, Reusable) data, cultural considerations relevant to that journey, and the potential future of scientific discovery if we reach the goal of FAIR.
Adam Kraut and Nicholas George at BioTeam, along with Sujaya Srinivasan at AWS, will cover strategies to transform, manage and analyze research-ready multimodal data using a cloud-based data lake.
Chris Dagdigian, BioTeam’s Co-Founder and Senior Technical Director of Infrastructure, will demonstrate how to integrate the popular commercial Schrödinger computational chemistry platform with AWS ParallelCluster.
Chris Dagdigian, BioTeam’s Co-Founder and Senior Technical Director of Infrastructure, candidly discussed how BioTeam uses AWS ParallelCluster to help our clients bring flexible, auto-scaling traditional HPC capabilities into the cloud.
BioTeam’s Laura Boykin, Senior Scientific Consultant, joins the roundtable webinar to discuss genomics and high-performance computing research and solutions for real world problems.
Dr. Ari Berman, CEO of BioTeam, reviewed the use cases for scientific computing (types of analytics, data storage, hardware capabilities, collaboration), the primary personas in most organizations that use and manage the technology, and the consequences and outcomes of making either the choice of Cloud or on-premises architectures.
