Data Science Insider: September 8th, 2023

In This Week’s SuperDataScience Newsletter: New Data Visualization Tool Showcases Electric Vehicle Jobs and Investments in US. Machine Learning Tool Simplifies The Formula of An Important Chemical Reaction. Machine Learning Reveals Human-Caused Climate Change’s Rainfall Disruption. NIH awards $5.8M to create Genomic Data Science Educational Hub. Understanding Data Science Critical for Life. Cheers, - The SuperDataScience Team P.S. Have friends and colleagues who could benefit from these weekly updates? Send them to [this link]( to subscribe to the Data Science Insider. --------------------------------------------------------------- [Data Visualization Tool Showcases Electric Vehicle Jobs and Investments in US]( brief: With the increase in demand for electronic vehicles and job shortages within the industry, the BlueGreen Alliance Foundation and Atlas Public Policy have discovered the ultimate solution. The companies have jointly released a new data visualization tool that provides a detailed and systematic overview of current electronic vehicle investments in the US. Known as the “EV Jobs Hub”, the tool has an easy-to-use, highly interactive dashboard. Overall, it encompasses the information on where various investments are being made, the distribution of unionized and non-unionized jobs within EV manufacturing, the industry trends, manufacturing specifications, and federal funding programs and subsidies. Structuring and displaying the data in accessible and transparent ways, the hub is an ideal resource for policymakers and the general public alike. “The EV Jobs Hub initiative seeks to cut through the noise from large announcements and organize it in a more digestible way,” Atlas Public Policy Senior Policy Analyst Tom Taylor said to the press. Why this is important: The EV Jobs Hub tool demonstrates how a data visualization tool can shape the policies regulating an entire industry. It is a key step to ensure that both state and federal governments are held accountable for their decisions regarding investments and programs and that their actions are effective in tackling the current shortage of high-quality, union jobs in the EV manufacturing sector and beyond. [Click here to learn more!]( [Machine Learning Tool Simplifies Formula of Important Chemical Reaction]( brief: Working together with chemists from “Hoffman La-Roche”, Illinois researchers Ian Rinehart and professor Scott Denmark have recently introduced an innovative machine learning tool that predicts the best conditions for the Butchwald-Hartwig reaction. Consisting of the carbon-nitrogen bond, this chemical reaction is widely used by pharmaceutical companies for making products. The new machine learning tool can estimate the most beneficial conditions for the reaction within minutes. Using an experimental dataset that contains the outcomes of various reactant pairings across a range of conditions, the founders were able to come up with a reliable and thoroughly tested predictive model. The code for the tool will be public and open-source. At the moment, the scientists are working on creating a cloud-based version, so that other researchers can add their own data to continue improving the workflow. Why this is important: There is no longer a need for lengthy and laborious experiments to discover the perfect conditions for the chemical reaction, as the tool simplifies and speeds up the process. Not only is this an important development for pharmaceutical companies, allowing them to streamline their production processes, it is also a great opportunity for academics who can use the tool for their own research. [Click here to read on!]( [Machine Learning Reveals Human-Caused Climate Change’s Rainfall Disruption]( In brief: In the last couple of decades, there’s been mounting evidence of the fact that climate change is human-caused and that the nation-states all over the world need to take measures immediately. These findings are now supported by a study undertaken by international researchers who used the machine learning tool to uncover the data of daily rainfall patterns. According to Tim Li, a co-author of the research study, they were able to establish that since the mid-2010s, there has been a clear disruption in the daily precipitation patterns across the tropical Eastern Pacific and mid-latitudes, directly attributed to human activity. The research suggests that these drastic fluctuations in the natural rainfall patterns are closely linked to the extreme changes in the weather in the last years, including heavy precipitation patterns, lengthy time periods without rain, and the occurrences of droughts, flooding, and fires. Why this is important: Not only does the vast data uncovered by the machine learning tool elucidates the need for urgent climate action globally, but it also highlights the need for localised research. These findings can act as a catalyst for solutions while taking into account the circumstances of the region, especially the island areas that are often the most affected. [Click here to discover more!]( [Data Science Educational Hub for Early Career Researchers]( In brief: Aiming to provide new learning opportunities for its students, the National Institutes of Health (NIH) will dedicate $5.8 million of its funding to establish a computational genomics and data science hub. The program will be available for those undertaking undergraduate and master's degrees. There will be workshops and hands-on sessions held to give students an opportunity to gain practical exposure within the genomic data science field. In particular, the NIH’s primary goal is to encourage students from diverse backgrounds, including those who may not have access to well-equipped computing facilities at their universities, to use the hub. “Instead of requiring their college or university to have its own high-performance computing infrastructure, students will be able to access genomic data and resources with only a laptop and an internet connection,” Shurjo Sen, program director in the Office of Genomic Data Science within the National Human Genome Research Institute (NHGRI), said in his statement. Why this is important: It is essential for educational institutions to address the issues of underrepresentation. Socio-economic and technological barriers are often the reason students from diverse backgrounds are prevented from entering the workforce on an equal footing with their more privileged counterparts. The ability to access genomic data sets and resources is vital for students and trainees to have a better grasp of genomic data research and analysis skills, which is also an integral part of their professional development. [Click here to see the full picture!]( [Understanding Data Science Critical for Life]( In brief: Carnegie Mellon University (CMU) has secured a grant from the Institute of Education Sciences to introduce a new initiative called Data Science for Education (DS4EDU). This program aims to train educators in the effective use of data analytics, assisting them in utilizing the vast amounts of learning data now available to improve teaching methodologies. The yearlong scheme includes a week of intensive training at CMU's LearnLab Summer School, followed by online coursework via CMU's Open Learning Initiative. The program's distinct feature is mentorship from numerous co-principal investigators, emphasizing hands-on experience in real-world educational settings. Why this is important: The DS4EDU initiative underscores the increasing significance of data-driven decision-making in education. By equipping educators with data analysis skills, there's potential to transform classroom methodologies and outcomes. This fusion of education and data science also broadens the field's impact, creating new avenues for research, collaboration, and tangible real-world application. [Click here to find out more!]( [Super Data Science podcast]( this week's [Super Data Science Podcast]( episode, host Jon Krohn explores with his guest Ajay Jain, Founder of Genmo.ai, how creative general intelligence could take the video industry by storm. They also discuss the models that got Genmo to this point, the applications of NeRF, and how understanding human psychology is so essential to developing models that output high-fidelity video. [Click here to find out more!]( --------------------------------------------------------------- What is the Data Science Insider? This email is a briefing of the week's most disruptive, interesting, and useful resources curated by the SuperDataScience team for Data Scientists who want to take their careers to the next level. Want to take your data science skills to the next level? Check out the [SuperDataScience platform]( and sign up for membership today! Know someone who would benefit from getting The Data Science Insider? Send them [this link to sign up.]( # # If you wish to stop receiving our emails or change your subscription options, please [Manage Your Subscription]( SuperDataScience Pty Ltd (ABN 91 617 928 131), 15 Macleay Crescent, Pacific Paradise, QLD 4564, Australia