Role requiring'No experience data provided' months of experience in None My name is Avdhesh Kumar and I am a Staffing Specialist at Intellectt Inc. I am reaching out to you on an exciting job opportunity with one of our clients.

Population imaging markedly increased the size of functional-imaging datasets, shedding new light on the neural basis of inter-individual differences. Analyzing these large data entails new scalability challenges, computational and statistical. For this reason, brain images are typically summarized in a few signals, for instance reducing voxel-level measures with brain atlases or functional modes. A good choice of the corresponding brain networks is important, as most data analyses start from these reduced signals. We contribute finely-resolved atlases of functional modes, comprising from 64 to 1024 networks. These dictionaries of functional modes (DiFuMo) are trained on millions of fMRI functional brain volumes of total size 2.4TB, spanned over 27 studies and many research groups. We demonstrate the benefits of extracting reduced signals on our fine-grain atlases for many classic functional data analysis pipelines: stimuli decoding from 12,334 brain responses, standard GLM analysis of fMRI across sessions and individuals, extraction of resting-state functional-connectomes biomarkers for 2,500 individuals, data compression and meta-analysis over more than 15,000 statistical maps. In each of these analysis scenarii, we compare the performance of our functional atlases with that of other popular references, and to a simple voxel-level analysis. Results highlight the importance of using high-dimensional "soft" functional atlases, to represent and analyse brain activity while capturing its functional gradients. Analyses on high-dimensional modes achieve similar statistical performance as at the voxel level, but with much reduced computational cost and higher interpretability. In addition to making them available, we provide meaningful names for these modes, based on their anatomical location. It will facilitate reporting of results.

ISELIN, N.J. -- JT Kostman, Ph.D., an internationally recognized leader in cognitive computing, applied artificial intelligence, and data strategy, has joined Grant Thornton LLP as managing director of applied artificial intelligence. In this new role, Kostman will lead the development and delivery of artificial intelligence, machine learning, IoT, blockchain, and advanced analytic solutions and services for the firm and Grant Thornton clients. He will be based in the firm's Iselin, N.J., office and will report into National Managing Principal of Innovation Kevin Baril. Kostman is a data scientist, mathematician and psychologist renowned for his expertise in applied artificial intelligence and cognitive computing. He boasts an impressive pedigree – having served as chief data officer and a member of the executive committee for Time Inc., chief data scientist for Samsung, and chief data scientist and big data psychologist for Aptus Insights.

Then consider this month's winners of the 2016 Siemens Competition, which honors math, science and technology projects from high school students around the country. These are some smart kids with plans to revolutionize fields such as medicine. Identical twin sisters from Texas won the $100,000 prize in the team event with their project that delivers an earlier diagnosis for schizophrenia. The $100,000 scholarship winner of the individual competition is from Oregon and he developed a biodegradable battery to power medical devices that you swallow. The sisters, Adhya and Shriya Beesam, are juniors (yes, juniors) at Plano East Senior High School in Plano, Texas, north of Dallas.