Given the wide range of applications and benefits offered by ML, there is a current push to implement it in the materials science sector, with many R&D-based organizations investing heavily in the development of digital strategies. However, one challenge these teams face is that scientific data is often complex and disconnected. This is a problem because ML systems rely on well-organized, high-quality data. So, how can you effectively apply ML to accelerate innovation and growth in your materials science company?
The promise of artificial intelligence has always felt more like a future state, but the reality is that many companies are already adopting AI initiatives. This is especially true in the scientific R&D realms. Over the last few years, there has been a huge increase of machine learning and AI initiatives in everything from QSAR models to genomics. According to a 2018 survey, AI adoption grew drastically from 38% in 2017 to 61% in 2018. This occurred across a variety of industries, including healthcare, manufacturing and financial services. However, most early adopters noted one of the biggest challenges to successful implementation involved data, specifically, accessing, protecting, integrating and preparing data for AI initiatives.
Celebrating its 10th year, the CAS Future Leaders program awards early-career scientists with essential scientific, business and leadership training and a trip to the ACS National Meeting & Exposition. This year, 29 participants from 16 countries took part in programming related to five leadership themes (Storytelling, Insights, Strategies, Perspectives and Impacts), all designed to help them advance their careers and make meaningful impacts in science.
About a year ago, I applied for CAS Future Leaders—an international program that aims to develop leadership skills and expand the professional network of Ph.D. students and postdoctoral researchers. As a grad student in my final year, I was especially excited to meet fellow scientists from similar international backgrounds
Have you heard about CAS Future Leaders? Since 2010, the program has provided early-career scientists with essential scientific, business and leadership training to help them make meaningful impacts in science. We're sharing "where are they now" stories written by our program alumni. This week's post features two alumni collaborating to elevate the scientific community in Malaysia, Felicia Lim (2018) and Magaret Sivapragasam (2017).
Have you heard about CAS Future Leaders? Since 2010, the program has provided early-career scientists with essential scientific, business and leadership training to help them make meaningful impacts in science. In the weeks to come, we're sharing "where are they now" stories written by our program alumni. This week's post features Fernando Gomollon Bel and Ben Naman, both participants in our 2014 program.
While there will always be need for I- and T-shaped professionals, most professionals today can't count on being really good at one thing to succeed. Organizations are increasingly seeking key-shaped candidates when recruiting new talent. So, how can individuals and organizations across industries become more key-shaped?
CAS, a division of the American Chemical Society specializing in scientific information solutions, announced today its CAS Life Sciences Advisory Board. The board comprises a world-class panel of global thought leaders, directing the CAS scientific journey to align authoritative content with groundbreaking predictive technologies that span the spectrum of life sciences workflows