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This study provides a comprehensive analysis of the AI-related skills and roles needed to bridge the AI skills gap in Europe. Using a mixed-method research approach, this study investigated the most in-demand AI expertise areas and roles by surveying 409 organizations in Europe, analyzing 2,563 AI-related job advertisements, and conducting 24 focus group sessions with 145 industry and policy experts. The findings underscore the importance of both general technical skills in AI related to big data, machine learning and deep learning, cyber and data security, large language models as well as AI soft skills such as problemsolving and effective communication. This study sets the foundation for future research directions, emphasizing the importance of upskilling initiatives and the evolving nature of AI skills demand, contributing to an EU-wide strategy for future AI skills development.
MULTIFILE
Whitepaper: The use of AI is on the rise in the financial sector. Utilizing machine learning algorithms to make decisions and predictions based on the available data can be highly valuable. AI offers benefits to both financial service providers and its customers by improving service and reducing costs. Examples of AI use cases in the financial sector are: identity verification in client onboarding, transaction data analysis, fraud detection in claims management, anti-money laundering monitoring, price differentiation in car insurance, automated analysis of legal documents, and the processing of loan applications.
Our unilateral diet has resulted in a deficiency of specific elements/components needed for well-functioning of the human body. Especially the element magnesium is low in our processed food and results in neuronal and muscular malfunctioning, problems in bone heath/strength, and increased chances of diabetes, depression and cardiovascular diseases. Furthermore, it has also been recognized that magnesium plays an important role in cognitive functioning (impairment and enhancement), especially for people suffering from neurodegenerative diseases (Parkinson disease, Alzheimer, etc). Recently, it has been reported that magnesium addition positively effects sleep and calmness (anti-stress). In order to increase the bioavailability of magnesium cations, organic acids such as citrate, glycerophosphate and glycinate are often used as counterions. However, the magnesium supplements that are currently on the market still suffer from low bio-availability and often do not enter the brain significantly.The preparation of dual/multiple ligands of magnesium in which the organic acid not only functions as a carrier but also has synergistically/complementary biological effects is widely unexplored and needs further development. As a result, there is a strong need for dual/multiple magnesium supplements that are non-toxic, stable, prepared via an economically and ecologically attractive route, resulting in high bioavailability of magnesium in vivo, preferably positively influencing cognition/concentration
Production processes can be made ‘smarter’ by exploiting the data streams that are generated by the machines that are used in production. In particular these data streams can be mined to build a model of the production process as it was really executed – as opposed to how it was envisioned. This model can subsequently be analyzed and stress-tested to explore possible causes of production prob-lems and to analyze what-if scenarios, without disrupting the production process itself. It has been shown that such models can successfully be used to diagnose possible causes of production problems, including scrap products and machine defects. Ideally, they can even be used to model and analyze production processes that have not been implemented yet, based on data from existing production pro-cesses and techniques from artificial intelligence that can predict how the new process is likely to be-have in practice in terms of data that its machines generate. This is especially important in mass cus-tomization processes, where the process to create each product may be unique, and can only feasibly be tested using model- and data-driven techniques like the one proposed in this project. Against this background, the goal of this project is to develop a method and toolkit for mining, mod-elling and analyzing production processes, using the time series data that is generated by machines, to: (i) analyze the performance of an existing production process; (ii) diagnose causes of production prob-lems; and (iii) certify that a new – not yet implemented – production process leads to high-quality products. The method is developed by researching and combining techniques from the area of Artificial Intelli-gence with techniques from Operations Research. In particular, it uses: process mining to relate time series data to production processes; queueing networks to determine likely paths through the produc-tion processes and detect anomalies that may be the cause of production problems; and generative adversarial networks to generate likely future production scenarios and sample scenarios of production problems for diagnostic purposes. The techniques will be evaluated and adapted in implementations at the partners from industry, using a design science approach. In particular, implementations of the method are made for: explaining production problems; explaining machine defects; and certifying the correct operation of new production processes.
Circular Economy is a novel disruptive paradigm redefining sustainability in the hospitality industry and addressing the environmental challenges set by this fast-growing impactful industry. To address these challenges, the creation of further knowledge on circular economy and its applications in the hospitality sector is fundamental, together with providing hoteliers and restaurateurs with proper skills and knowhow to tackle such challenges. Drawing on a on going pilot project on Circular Economy in Hotels in Amsterdam, the Friesland hospitality sector and the Professorship of Sustainability in Hospitality and Tourism at NHL Stenden University of Applied Sciences have set out to develop an innovative learning experimental environment in which Friesland hoteliers and restaurateurs can develop further knowledge and identify - together with students, researchers, and experts – possible key actions and strategies to implement regenerative circular processes of material up-cycling. To which extent this learning community of the Northern Netherlands contributes to develop wider knowledge on circular economy in hospitality and to identify, implement, and test innovative regenerative circular actions will be evaluated.
