The HPC Digital Autonomy with RISC-V in Europe (DARE) will invigorate the continent’s High Performance Computing ecosystem by bringing together the technology producers and consumers, developing a RISC-V ecosystem that supports the current and future computing needs, while at the same time enabling European Digital Autonomy. DARE takes a customer-first approach (HPC Centres & Industry) to guide the full stack research and development. DARE leverages a co-design software/hardware approach based on critical HPC applications identified by partners from research, academia, and industry to forge the resulting computing solutions. These computing solutions range from general purpose processors to several accelerators, all utilizing the RISC-V ecosystem and emerging chiplet ecosystem to reduce costs and enable scale. The DARE program defines the full lifecycle from requirements to deployment, with the computing solutions validated by hosting entities, providing the path for European technology from prototype to production systems. The six year time horizon is split into two phases, enabling a DARE plan of action and set of roadmaps to provide the essential ingredients to develop and procure EU Supercomputers in the third phase. DARE defines SMART KPIs for the hardware and software developments in each phase, which act as gateways to unlock the next phase of development. The DARE HPC roadmaps (a living document) are used by the DARE Collaboration Council to maximize exploitation and spillover across all European RISC-V projects. DARE addresses the European HPC market failure by including partners with different levels of HPC maturity with the goal of growing a vibrant European HPC supply chain. DARE Consortium partners have been selected based on the ability to contribute to the DARE value chain, from HPC Users, helping to define all the requirements, to all parts of the hardware development, software development, system integration and subsequent commercialization.

Kinases are key regulators of protein activity and phosphorylate thousands of proteins in cells. The phosphoproteome can hence be viewed as a proxy for the proteome activity status of a cell. Dysregulation of the phosphoproteome can cause diseases such as cancer. As a result, kinase inhibitors have become important drugs in oncology and nearly 50 are approved for use in humans. As they typically have a range of targets, there is enormous potential for repurposing these drugs for other cancer entities. To implement this in the clinic, it is important to better understand: i) how the phosphoproteome of an individual tumor can be functionally interpreted, ii) how and to what extent kinase inhibitors modulate the phosphoproteome and iii) which drug is the best fit for modulating the proteome activity status of a particular tumor. This information is only partially or not available from classical cancer diagnostics or genomics. Therefore, the central aim of this project is to show that ground breaking new information for the diagnosis and treatment of cancer patients will come from measuring their tumor proteome activity status (TOPAS) by quantitative mass spectrometry. To this end, the first objective is to show that modulating the TOPAS of cancer model systems by kinase inhibitors functionalizes the phosphoproteome and reveals the cellular mechanisms of action of these important medicines. The second objective is to develop and validate diagnostic drug-, protein- and pathway-centric TOPAS scores able to make treatment suggestions based on the phosphoproteomes of cancer models and tumor tissues. The third objective is to demonstrate, on the example of sarcoma patients, that TOPAS scoring adds value to decision making by molecular tumor boards. Combining the strengths of proteomics and genomics, I aim for building a comprehensive multi-omics view on tumors and will create a ‘virtual tumor board’ in ProteomicsDB to make TOPAS available to the scientific community.

The biological engineering project EMcapsulins will create the first suite of multiplexed genetic reporters for electron microscopy (EM) to augment today’s merely structural brain circuit diagrams (connectomes) with crucial information on neuronal type and activation history. My team will generate this new toolbox based on genetically encoded nanocompartments of the prokaryotic ‘encapsulin’ family that we have recently shown to enable genetically controlled compartmentalization of multicomponent processes in mammalian cells. By encapsulating metal-organizing cargo proteins in the lumen of the semi-permeable encapsulin nanospheres, they serve as fully genetic EM gene reporters (EMcapsulins) that provide robust and spatially precise contrast by conventional EM in mammalian cells. To enable geometric multiplexing in EM in analogy to multi-color light microscopy, we will explore the large geometrical feature space of EMcapsulins to establish three core Functionalities: ① different shell structures and diameters, ② modular and tunable shell functionalizations, and ③ multiplexed and triggered cargo loading. We will combine these Functionalities to produce geometrically multiplexed EMcapsulin markers of neuronal identity in serial EM (Application ❶). We will also engineer EMcapsulin reporters for activity-dependent gene expression, calcium signaling, and synaptic activity that can ‘write’ geometrically encoded records of neuronal activation history into EM connectomics data (Application ❷). These ‘multi-color’ and modular EMcapsulin markers and reporters deliver the missing bridging technology between time-resolved light microscopy measurements of neuronal activation dynamics and structural EM connectomics data. EMcapsulin technology will convert structural to functional EM connectomes to enable a systematic analysis of how brains write molecular signaling dynamics into structural patterns to store information for later retrieval.

LaserCell envisions an innovative approach to reshape and rearrange cellulose at the molecular level by disrupting cohesive interactions through resonant excitation of specific bonds. It will revolutionize the field of biopolymer processing beyond cellulose and yield fundamental insights into supramolecular structure and dynamics in biomaterials. Although cellulose is biodegradable and mechanically strong, it cannot be processed by conventional thermoplastic polymer methods, which limits its use as high-volume material. Cellulose decomposes before it melts because of cooperative intermolecular hydrogen bonding and hydrophobic interactions. To plasticise cellulose, I propose to disrupt these intermolecular bonds with photon energy delivered by infrared (IR) laser pulses. Employing wavelengths matching specific vibrational modes, the photon energy will be resonantly absorbed, thus effectively plasticising cellulose. I envision that the rapid energy dissipation in short pulses will deliver enough peak power to disrupt the intermolecular bonds yet avoiding thermal damage. I plan to systematically investigate how laser parameters influence the supramolecular structure of cellulose and establish analytical tools to characterize its structural transitions under mechanical load. Additionally, to allow processability in different set-ups, I aim to prolong the time window of plasticization and adjust the flowability, by using the laser irradiation in synergy with the hydrogen disrupting molecules. As a proof of concept, I will implement this novel photo-plasticization technique into a cellulose fibre spinning process and post-treatment to modulate the cellulose fibre crystallinity. I have worked for 10 years on cellulose-based materials and have a strong background in fibre spinning and material science. My research group will engage 1 PhD student and 2 Postdocs with background in polymer science and laser physics and technology.

DNA has a huge potential for the long-term storage of large amounts of data. However, writing, editing, and reading DNA-based data is expensive and inefficient with current technologies. Our vision is to develop a low-cost, energy-efficient, and fast data drive that is able to write, edit, store, and retrieve DNA-based data. The data drive is based on simple and easily available hardware components plus bacterial cells. The proposed technological solution enables the short-, medium-, and long-term storage of DNA-based data. To achieve this vision, we will exploit bacterial genetic mechanisms that were evolutionarily optimized for billions of years, such as colour-sensitive genetic switches and DNA exchange processes. We have defined two specific objectives to achieve our goal. As a proof-of-concept, we will store a large trajectory file of a molecular dynamics simulation encoded on DNA. Our consortium has six partners from four European countries. One research organisation, two university, and two SMEs will work together to achieve the outlined vision.