RCaz/eu-funding-proposals-sft huggingface dataset:
system: You are an expert grant writer specializing in European Union research funding proposals. You write compelling, well-structured proposal sections that demonstrate excellence, impact, and implementation quality, using precise EU terminology and following best practices for Horizon Europe, Horizon 2020, and earlier framework programmes.

user: Compose the 'Concept and Approach' section for a Horizon 2020 proposal on 'Translational approaches to disease modifying therapy of type 1 diabetes - HARVESTing the fruits of INNODIA'.

assistant: **Concept**

Building on the strong foundations of INNODIA, with its unique, Europe-wide clinical and basic research network for the study of type 1 diabetes (T1D), we propose in INNODIA HARVEST an ambitious program which aims to prevent and arrest T1D via focused objectives targeting consolidation and innovation. First, we will consolidate the INNODIA clinical network as the reference point for conducting studies to prevent or arrest T1D. We will transform our standardized clinical and bioresource platforms into a high-performance clinical trial network, running academic and industry-driven trials alongside small, mechanism-centric, biomarker-rich intervention trials to examine pathobiological pathways to T1D. INNODIA HARVEST will conduct two large studies to arrest T1D at its onset, one academia-driven, beta-cell focused (VER-A-T1D, verapamil) and one industry-driven, immune-focused (Iscalimab-study). We will exploit our original INNODIA Master Protocol allowing novel adaptive trial design to introduce combination therapies that build on complementary mechanisms. Second, we will extend our study design strategy by introducing novel biomarkers, both clinical (continuous glucose monitoring) and experimental (microbiome analysis) to deconvolute disease heterogeneity and identify new endpoints to accelerate identification of effective therapeutics. Third, we will use ‘disruptors’ in small mechanistic studies to channel innovation from clinic to basic research through a reverse immunology and reverse beta-cell biology approach. Finally, we will implement new discovery pipelines for future therapeutics, exploiting tools such as iPSC-derived islet-like cells to promote next generation target identification and drug development. As in INNODIA, the voice of people living with T1D and their
system: You are an expert grant writer specializing in European Union research funding proposals. You write compelling, well-structured proposal sections that demonstrate excellence, impact, and implementation quality, using precise EU terminology and following best practices for Horizon Europe, Horizon 2020, and earlier framework programmes.

user: Write a project proposal abstract for 'Epithelial Memory to Candida albicans during commensalism and infection' to be submitted under Horizon Europe.

assistant: **Abstract**

In this research project I seek to discover the mechanisms underlying oral epithelial cell (OEC) memory and its importance to control Candida albicans infections and commensalism. C. albicans is part of the healthy microbiota, but it is also the most clinically relevant fungus. Fine tuning of mucosal immunity enables homeostasis and regulates commensal-to-pathogen transition of C. albicans. Innate immune cells, such as macrophages, can develop long-term responses during systemic infections, enabling them to clear invading microbes more efficiently. This so-called process of “innate immune memory” can be targeted in order to improve patient outcomes. However, at the oral mucosa, where immune cells are more scarce, OECs are essential for controlling fungal growth and orchestrating complex immune responses. Whilst OEC-C. albicans interactions have been well analysed during acute infections, no study up to date has addressed epithelial memory or its impact on fighting fungal infections and regulating Candida commensalism.The aim of this project is to understand the molecular and cellular mechanisms driving epithelial memory in response to C. albicans. In preliminary in vitro studies, I have shown that epithelial memory protects OECs from C. albicans and therefore, I hypothesised that this phenomenon control fungal growth during pathogenesis and homeostasis. I will use advanced models of host-microbe interactions to confirm the importance of epithelial memory for clearing infections and whether it promotes fungal commensalism by regulating microbial growth. I will decipher the underlying molecular mechanisms by analysing gene expression and metabolic profiles of memory cells, and identify potential targets that promote homeostasis at the oral mucosa.This project will yield n
system: You are an expert grant writer specializing in European Union research funding proposals. You write compelling, well-structured proposal sections that demonstrate excellence, impact, and implementation quality, using precise EU terminology and following best practices for Horizon Europe, Horizon 2020, and earlier framework programmes.

user: Write the concept and methodology overview for 'Occupational exposures as risk factors for congenital malformations' under Fourth Framework.

assistant: **Concept**

Foreseen ResultsAssemble about 1000 cases of selected non-genetic malformations detected in newborns in the first week of life and 2000 control pregnancies. Assess the occupational risks by independently reviewing the work exposures of the mothers and where possible identify the likeley substances involved. Combine some of the results of this study in Bratislava, Budapest and Lublin with the earlier case-control study in western european countries to confirm or refute risk factors for congenital malformations. Publicise the results with a view to initiating preventive strategies in the workplaces of the EC and in eastern Europe.There has been a slow increase in the understanding of risk factors arising in the workplace which may increase the rates of congenital malformations in the babies of working women. However for the vast majority of malformations (excluding those of genetic or known cause) there are large variations in rates between different centres. Some of the reasons for this are likely to reside in the general environment, in particular in the working environment of women and men.Building on the experience of a large co-operative study in four countries of the EU an extension of the methodology is proposed to cover three countries of the CCE. This will allow the maximization of the experience already gained, the transfer of the experience between further participants, and the inclusion of study areas in which exposure to potential hazardous substances in the workplace is much less controlled than in western Europe. There is an element of urgency to study risk factors where exposures are higher in CCE countries than in many developed countries before they are reduced by increasing control over the working environment. It is easier to measure effects of high ex
system: You are an expert grant writer specializing in European Union research funding proposals. You write compelling, well-structured proposal sections that demonstrate excellence, impact, and implementation quality, using precise EU terminology and following best practices for Horizon Europe, Horizon 2020, and earlier framework programmes.

user: Describe the novelty, innovation potential and advance beyond the state of the art for 'First economically-viable process for phosphate recovery' (SusPhos).

assistant: **Innovation**

The EU has listed phosphorus (P) and phosphate rock as a critical raw material due to supply uncertainties related to 90% imported rock phosphate imports. 90% of used P is irreversibly lost. Our solution converts P rich waste streams, e.g., sewage sludge ashes (SSA) and struvite, into phosphoric acid used in the fertilizer and flame retardant industries and chemicals for wastewater treatment and the construction industry. SusPhos will create Europe's independent supply of P. Flame retardants (FR) and fertilizer industries will readily consume these high-value products. Halogenated FRs are toxic and the manufacturers are switching from halogen-based ingredients to phosphates derived from rock phosphate. There are no methods that can upcycle P-rich SSA for direct use by FR and fertilizer manufacturers that use 3.4M t of phosphates worth €1.84B. By 2026, SusPhos will earn €43.9M p.a. with the potential to displace 20% of conventionally produced phosphates and eliminate 3.9M tonnes of CO2.


**Keywords:** Phosphorus chemistry,Phosphate fertilizers,Struvite,Sewage sludge ash,Phosphate flame retardants,Phosphorus recycling,Circular chemistry,Urban mining
system: You are an expert grant writer specializing in European Union research funding proposals. You write compelling, well-structured proposal sections that demonstrate excellence, impact, and implementation quality, using precise EU terminology and following best practices for Horizon Europe, Horizon 2020, and earlier framework programmes.

user: Explain how 'Growing Machines Capable of Rapid Learning in Unknown Environments' goes beyond current state-of-the-art under Horizon Europe.

assistant: **Innovation**

Despite major advances in the field of artificial intelligence, especially in the field of neural networks, these systems still pale in comparison to even simple biological intelligence. Current machine learning systems take many trials to learn, lack common-sense, and often fail even if the environment only changes slightly. The enormous potential of autonomous machines remains unfulfilled and we still lack robots to fill our dishwashers or go on autonomous search-and-rescue missions. The grand goal of GROW-AI is to create machines with a more general intelligence, allowing rapid adaption in unknown situations. In stark contrast to current neural networks, whose architectures are designed by human experts and whose large number of parameters are optimized directly, evolution does not operate directly on the parameters of biological nervous systems. Instead, these nervous systems are grown and self-organize through a much smaller genetic program that produces rich behavioral capabilities right from birth and the ability to rapidly learn.  Neuroscience suggests this ""genomic bottleneck"" is an important regularizing constraint, allowing animals to generalize to new situations. However, currently there does not exist a solution to creating a similar system artificially. We address this challenge with two ambitious ideas. First, we will learn genomic bottleneck algorithms instead of manually designing them,  exploiting recent advances in memory-augmented deep neural networks that can learn complex algorithms.  In addition, we will co-optimize task generators that provide the agents with the most effective learning environments. Taking inspiration from the fields of artificial life, neurobiology, and machine learning, we will investigate if algorithmic growth is needed to
system: You are an expert grant writer specializing in European Union research funding proposals. You write compelling, well-structured proposal sections that demonstrate excellence, impact, and implementation quality, using precise EU terminology and following best practices for Horizon Europe, Horizon 2020, and earlier framework programmes.

user: Write the 'Expected Impact' section for the project 'CRITICAL RESOURCE SHARING FOR COOPERATION IN COMPLEX SYSTEMS' (CRESCCO), addressing dissemination and exploitation.

assistant: **Impact**

The integration in modern Information and Communication Technologies of:i) heterogeneous communication infrastructures (optical, ATM networks);ii) mobile users accessing these backbone networks and the Internet, and;iii) dynamic selfish agent entities, results in highly dynamic, complex, global systems. To design and implement high-speed, cost-effective, and reliable communication and computing solutions for such environments, we investigate the bottleneck and critical issues involved at the fundamental algorithmic level. In particular, we focus on the efficient management of scarce and critical resources such as frequency spectrum and energy in wireless networks, bandwidth in optical and ATM networks, as well as CPU time, space and communication time in dynamic environments of selfish agents. We pursue a multidisciplinary approach that combines and extends techniques from computer science, economics and operations research.OBJECTIVESThis project investigates at a foundational level the critical aspects and bottlenecks arising in highly dynamic and extremely complex global systems emerging from the integration of heterogeneous communication infrastructures, highly dynamic mobile user populations and dynamic selfish agent entities. We focus on the efficient management of limited and scarce communication and computing resources to ensure co-operation and efficient access to advanced services in such environments by investigating the design and implementation of high-speed, cost-effective and reliable communication and computing solutions.DESCRIPTION OF WORKWe investigate the underlying, fundamental, algorithmic and complexity-theoretic aspects of co-operation and optimisation in dynamic, complex, global environments, by providing efficient, robust and scalable algorithmic
system: You are an expert grant writer specializing in European Union research funding proposals. You write compelling, well-structured proposal sections that demonstrate excellence, impact, and implementation quality, using precise EU terminology and following best practices for Horizon Europe, Horizon 2020, and earlier framework programmes.

user: Compose the 'State of the Art and Innovation' section for a Horizon Europe proposal on 'FAME: OPEN-ENDED MANIPULATION TASK LEARNING WITH FAME (FUTURE-ORIENTED COGNITIVE1 ACTION MODELLING ENGINE)'.

assistant: **Innovation**

The realization of computational models for accomplishing everyday manipulation tasks for any object and any purpose would be adisruptive breakthrough in the creation of versatile, general-purpose robot agents; and it is a grand challenge for AI and robotics.Humans are able to accomplish tasks such as “cut up the fruit” for many types of fruit by generating a large variety of context-specificmanipulation behaviors. They can typically accomplish the tasks on the first attempt despite uncertain physical conditions and novelobjects. Acting so effectively requires comprehensive reasoning about the possible consequences of intended behavior beforephysically interacting with the real world.In the FAME project, I will investigate the research hypothesis that a knowledge representation and reasoning (KR&R) frameworkbased on explictly-represented and machine-interpretable inner-world models can enable robots to contextualize underdeterminedmanipulation task requests on the first attempt. To this end, I will design, implement, and evaluate FAME (Future-oriented cognitiveAction Modelling Engine), a hybrid symbolic/subsymbolic KR&R framework that will contextualize actions by reasoning symbolicallyin an abstract and generalized manner but also by reasoning with “one’s eyes and hands” through mental simulation and imagisticreasoning. Realizing FAME requires three breakthrough research results:(1) modelling and parameterization of manipulation motion patterns and understanding the resulting effects underuncertain conditions;(2) the ability to mentally simulate imagined and observed manipulation tasks to link them to the robot’s knowledge and experience;and(3) the on-demand acquisition of task-specific causal models for novel manipulation tasks through mental physics-based simulations
system: You are an expert grant writer specializing in European Union research funding proposals. You write compelling, well-structured proposal sections that demonstrate excellence, impact, and implementation quality, using precise EU terminology and following best practices for Horizon Europe, Horizon 2020, and earlier framework programmes.

user: Describe how 'JUPITER AI Factory' will create measurable scientific, societal and economic impact aligned with Horizon Europe.

assistant: **Impact**

JAIF, the JUPITER AI Factory, is set to become a core element of the European innovation cluster of AI factories that is being created to accelerate the development and deployment of AI solutions by utilising Europe's powerful HPC infrastructure, particularly across industries with their growing demand. JAIF will act as a one-stop shop with a single point of contact, focusing on the support of European start-ups, small and medium-sized enterprises, industrials, the public sector and scientific research.A consortium of leading institutions with AI experience has joined forces in JAIF around JUPITER, the first exascale supercomputer in Europe. JAIF’s partners are the Jülich Supercomputing Centre at Forschungszentrum Jülich (JSC at FZJ), the Center for Artificial Intelligence at RWTH Aachen University (AI Center), the Fraunhofer Institutes for Applied Information Technology (FIT) and for Intelligent And Information Systems (IAIS), and the Hessian Center for Artificial Intelligence (hessian.AI).JAIF will be a cornerstone of Europe’s AI innovation ecosystem, leveraging the capabilities of the JUPITER exascale supercomputer to accelerate AI development and deployment. By providing a one-stop shop for start-ups, SMEs, industrials, JAIF supports innovation across key sectors, while ensuring GDPR compliance and trustworthy AI practices. With a consortium of leading institutions and an ambitious service portfolio, JAIF addresses the growing demand for AI solutions, bridges gaps in expertise, fosters collaboration across Europe, and strengthens Europe's position as leader in AI-driven prosperity and growth.As part of JAIF, JUPITER will be extended with the inference system JARVIS.


**Keywords:** AI, HPC, Inference, Startups, SMEs, Industry, Research
system: You are an expert grant writer specializing in European Union research funding proposals. You write compelling, well-structured proposal sections that demonstrate excellence, impact, and implementation quality, using precise EU terminology and following best practices for Horizon Europe, Horizon 2020, and earlier framework programmes.

user: Write the concept and methodology overview for 'Materials  Technologies for performance improvement of Cooling Systems in Power Plants' under Horizon 2020.

assistant: **Concept**

MATChING goal is the reduction of cooling water demand in the energy sector through innovative technological solutions, to be demonstrated in thermal and geothermal power plants. The project targets include an overall saving of water withdrawal of 30% in thermal power generation, and a decrease of evaporative losses up to 15% in geothermal sector. The use of advanced and nano-technology based materials will be leveraged to make economically affordable water saving in power plants and pave the way to the market uptake. All technological areas of plant cooling systems will be affected: cooling tower, steam condenser, cooling water circuit and water conditioning. The use of alternative cooling fluids will be investigated to develop advanced hybrid cooling towers for geothermal high temperature power plants, and hybrid cooled binary cycles for low temperature geothermal fields, combining dry/wet cooling, and closed loop groundwater cooling. To increase available effective water supply at reasonable costs, alternative water sources will be exploited: different membrane based technologies will be used to re-cycle or re-use municipal, process and blow down waters. To improve cooling equipment robustness advanced materials and coatings for cooling tower and condensers will be investigated, allowing increasing concentration cycles or directly using aggressive fluids. Demonstration will take place in partner-owned industrial sites, operating pilot plants in intended environment and/or in demo scale, guaranteeing the achievement of TRL 6 for all the technologies. The demonstration activities and the partnership composition ensures the validation of suitable business models and the finalization of business plans, guaranteeing the technological transfer from industry to market, incr
system: You are an expert grant writer specializing in European Union research funding proposals. You write compelling, well-structured proposal sections that demonstrate excellence, impact, and implementation quality, using precise EU terminology and following best practices for Horizon Europe, Horizon 2020, and earlier framework programmes.

user: Describe the specific objectives and expected outcomes for 'Biologically-motivated probabilistic evolutionary models and their use for genomic analyses' in the context of a Seventh Framework call.

assistant: **Objectives**

Probabilistic evolutionary models have revolutionized the way sequence data are handled. The success of such models in sequence analysis resides in their ability to accurately describe the stochastic evolutionary process and to incorporate key biological phenomena as they are being discovered. Codon models, in particular, have been indispensable for meaningful biological analysis of vast amount of data because they allow differentiating between the types of selective forces that operate on the genome. Specifically, codon evolutionary models are often used for two related challenges: to detect selective forces operating on protein-coding genes and to study the association of such forces with species’ characteristics. Here, I propose developing and applying novel codon models to tackle these challenges from new perspectives. My suggested models are biologically realistic, computationally feasible, and preliminary data show that they fit sequence data better than previously available models. More specifically, the newly proposed models will relax the widespread unrealistic assumption that synonymous substitutions are free from selection. This will be achieved by explicitly accounting for the baseline selection forces acting at the RNA and DNA levels, on top of which the selection at the amino-acid level operates. This has important implications not only for positive selection inference, but also for the detection of functional elements that operate at the nucleotide level. I further propose developing a unified codon model for the analysis of phenotype-genotype evolution. This novel approach would allow inferring the relative roles of selection and mutation in causing substitution rate variation of a particular gene associated with a particular trait. The use of this novel