EU funded projects
Marie Skłodowska-Curie Actions
Innovative Training Networks (ITN) / Doctoral Networks as Coordinating Institution
ALPACA
Algorithms for analyzing millions of genomes simultaneously
While all different, genomes from the same species agree in the vast majority of places. This asks some intriguing questions to computer scientists: what data structures and algorithms can we employ to store and analyze millions of genomes from one species in a resource- and real-world-application friendly manner? The EU International Training Network ALPACA, coordinated by Alexander Schönhuth, deals with these problems, and trains a new generation of computer scientists who are able to think and work in terms of the new structures and algorithms developed.
CoRDS
The CoRDS project addresses building the next generation of artificial intelligence (AI)-powered decision support tools to allow organizations to tackle complex decision-making problems more effectively and responsibly, such as efficiently managing scarce (natural) resources and reducing their carbon footprints. These tools unify two areas of research, namely Operations Research (OR) and Machine Learning (ML). In OR, specialized optimization methods have been developed to address complex decision problems, but these rely heavily on expert knowledge, limiting their ability to adapt to changing data. Conversely, ML excels in leveraging extensive data for predictive tasks, but struggles with combinatorial optimization. Integrating OR and ML, leading to data-driven optimization (DDO) tools, presents a promising avenue to enhance decision support by combining OR's problem-solving capabilities with ML's data utilization strengths. Furthermore, DDO tools must not only provide high-quality decisions to users in low computational time, they must also comply with government and industry standards, and therefore must be safe, transparent, traceable and non-discriminatory, i.e., follow the principles of trustworthy AI, a significant challenge for most current AI systems. The expertise needed to create and apply DDO methods to real-world problems is severely lacking. The CoRDS doctoral network addresses this critical need by developing a training program to sculpt the next generation of analytics experts combining OR and ML, who will translate their research into prototype tools to address real-life problems defined in collaboration with our industrial partners across various application sectors, including logistics, healthcare, public transportation, production, finance, publishing and machine translation. The CoRDS network further delivers a training framework for others to use and expand.
EPOC
How can society and politics deal with challenges that are characterised by high uncertainty, great complexity and dynamic change? There are many examples of this, such as climate change or the development and dissemination of technical innovations. The Innovative Training Network EPOC ("Economic Policies in Complex Environments") promotes the development and application of modern computer-based models and analysis methods that are suitable for soundly analysing the effects of policy measures and providing decision support even in complex and challenging environments. EPOC pursues this goal by combining an interdisciplinary research agenda with an innovative doctoral programme developed and run jointly by several European universities.
Magicbullet::Reloaded
Targeting tumour cells
Despite constant development of new and more efficient treatment methods, cancer remains the second most common cause of death worldwide. Paul Ehrlich, Nobel Prize winner for physiology in 1908, had a vision early on of a targeted drug, a so-called "magic bullet", which would attack only the tumour cells and spare healthy cells. The European Training Network "Magicbullet::Reloaded", coordinated by chemist Prof. Dr. Norbert Sewald, continues Ehrlich's visionary concept and develops conjugates of active substances with peptides or small molecules that are able to specifically target tumour cells.
Innovative Training Networks (ITN) / Doctoral Networks as Partner
- CAVECORE
Title: Continuous, Automated Validation, and Evaluation of Cognitive Robots in Open-Ended Environments
PI: Prof. Dr. Klaus Neumann
Faculty of Technology
Summary:
What technology can enable more agile production, personalized healthcare, efficient logistics, and expand scientific reach into ocean depths? We need cognitive robots that interact with environments, humans, and agents to autonomously acquire skills and perform diverse tasks in open-ended contexts. CAVECORE addresses a critical challenge in AI-enabled robotics: evaluating the quality of robotic agents in open-ended environments, including performance, safety, and reliability. How can we validate robot behavior with trustworthy measurements and automate this task over long periods? CAVECORE aims to streamline the innovation process into goal-oriented, efficient technological progress for organizations developing cognitive robots by training AI robotics researchers in methods for replicable, unbiased validation and evaluation in virtual and real-world environments, allowing humans to calibrate trust towards cognitive robots. CAVECORE enables stakeholders (users, developers, policymakers) to understand the expected and actual quality of cognitive robots, ensuring conformance with emerging ethical, legal, social, and economic requirements of the EU AI Act, and delivering robots capable of continuous self-assessment and improvement. CAVECORE's principle of evaluability-by-design mandates that validation and evaluation concepts be integral to the robot development process, not an afterthought, and that cognitive robots continuously provide evidence of their quality. This principle shapes the training program and expert consortium, which offers interdisciplinary training in cognitive science and robotics, AI metrology, and automated testing and validation.
Duration: 01.09.2025 – 31.08.2029
- ESSGN
Title: European Social Science Genetics Network
PI: Prof. Dr. Martin Diewald
Faculty of Sociology
Summary:
The European Social Science Genetics Network (ESSGN) brings together seven academic beneficiaries with a shared interest in social science genetics, i.e. in incorporating genetic information to improve our understanding of age-old questions in the social sciences, such as the origins of inequality, the 'nature versus nurture' debate, and the extent to which the interplay between environments and genes is important in shaping individuals' lives. The consortium consists of an interdisciplinary group of academics, as well as seven non-academic partners committed to using data Science to address inequalities in life chances. There is an urgent need for training in social science genetics due to recent technological advances in genetics, the intricacies of using genetic data, and the growing availability of such data in surveys traditionally studied by social scientists. Our aim is to train the next generation of social scientists in the responsible and technically correct use of genetic data and in objective communication about what can and cannot be learned from working with genetic data in the social sciences.
The project will go beyond the state-of-the-art (i) by using Europe's most comprehensive multigenerational databases to separate direct genetic effects from parental genetic and socio-economic factors that shape the rearing environment; and (ii) by exploiting the large toolbox of causal inference methods used in econometrics and statistics to estimate the extent to which environments causally protect individuals with genetic disadvantages. We will (1) analyse to what extent genetic ('nature') and environmental ('nurture') factors contribute to equality of opportunity and intergenerational mobility, and (2) establish how nature and nurture jointly shape inequalities in life chances. As such, our programme of research provides novel and exciting opportunities to social scientists to deepen our understanding of how inequalities in life chances are shaped.Duration: 03.2023-02.2027
- ImAge-D
Title: Imaging Ageing Endothelium at the nanoscale - Doctorates
PI: Prof. Dr. Thomas Huser
Faculty of Physics
Summary:
ImAge-D will train a new generation of Doctoral Candidates (DCs) in the development and application of newly developed high speed and high-resolution imaging tools in biomedical research. The ten DCs will be cross-pollinated with concepts and skills in physics and biomedicine, in particular in super-resolution imaging, analytical image reconstruction, and optical micro-manipulation methods. These skills will be applied to reveal for the first time the functionality and morphology (below the diffraction limit of light) of living endothelial cells (EC) that present the main barrier between the blood/lymph and all organs and tissues, and how these vital cells change with ageing. Very little is known at the nanoscale about extremely important physiological functions of EC and their role in the transfer and/or clearance of metabolites and pharmaceuticals to vital organs, and how EC change with ageing. The current generation of optical nanoscopes, however, is rather slow and can only be applied to isolated, typically fixed (i.e. dead) cells rather than biomedically relevant tissues. Also, newcomers to the field need to familiarize themselves with a whole new set of potential problems that might arise in the use of optical nanoscopy, such as image reconstruction- related artifacts to name just one example.This is an area of research where European enterprises are very active. Excellent training in new scientific and complementary skills, combined with international and intersectoral work experience, will instill an innovative, creative and entrepreneurial mind-set in ImAge-D's DCs, maximising economic benefits based on scientific discoveries. These specialised, highly trained, and mobile DCs will have greatly enhanced career prospects. The training in novel physical methods with highly relevant experience in the biomedical sciences will allow them to confidently navigate at the interface of academic, clinical and private sector research.
Duration: 10.2023-09.2027
- LEMUR
Title: Learning with Multiple Representations
PI: Prof. Dr. Barbara Hammer
CITEC - CENTER FOR COGNITIVE INTERACTION TECHNOLOGY
Abstract:
Machine learning methods operate on formal representations of the data at hand and the models or patterns induced from the data. They also assume a suitable formalization of the learning task itself (e.g. as a classification problem), including a specification of the objective in terms of a suitable performance metric, and sometimes other criteria the induced model is supposed to meet. Different representations or problem formalizations may be more or less appropriate to address a particular task and to deal with the type of training information available. The goal of LEMUR is to create a novel branch of machine learning we call Learning with Multiple Representations. We aim to develop the theoretical foundations and a first set of algorithms for this new paradigm. Moreover, corresponding applications are to demonstrate the usefulness of the new family of approaches. We regard LEMUR as very timely, as LMR algorithms will allow to flexible representations (e.g. suitable for explainability, fairness) with diverse target functions (e.g. incorporating environmental or even social impact) as well as to make the induced models abide by the Green Charter and trustworthy AI criteria by design. We will focus on learning with weak supervision because it addresses one of the major flaws of modern ML approaches, i.e. their data hunger, by means of weaker sources of labelling for training data. The outcome of the DN will be a set of 10 experts trained to implement the third and subsequent waves of AI in Europe. The highly interdisciplinary and intersectoral context in which they will be trained will provide them with research-related and transferable competences relevant to successful careers in central AI areas.
Duration: 01.2023-12.2026
- MolCal
Title: Molecule-based magneto/electro/mechano-Calorics
PI: Prof. Dr. Jürgen Schnack
Department of Physics
Abstract:
MolCal will contribute to establishing a critical mass of researchers in promising exploratory topics on caloric materials and energy conversion technologies for solid-state cooling and heating applications at near-ambient and very-low temperatures. Temperature control systems are responsible for approximately half of the EU energy consumption expenditure. This figure alone amply justifies the need to dedicate great efforts to the search for alternative refrigeration and heat pump methods. Research on caloric materials has never been as active as it is now, due to the prospect of new-generation refrigerators and heat pumps that are energy efficient and environmentally friendly, on the one hand, and the policies on low-energy consumption and global warming refrigerants, on the other. MolCal presents an approach never tried before in similar collaborative research training programmes. We will consider caloric materials that fall under the umbrella of molecule-based materials and can respond to different sources of the driving stimulus, be it magnetic, electric, and/or mechanical. Since there is no clear-cut consensus on which type of caloric material holds the most promise, this multi-front approach will be an advantage because it will permit transfer of methods already developed from the magnetocaloric subfield into the others, which are increasingly in the spotlight because of their enormous potentiality. Furthermore, MolCal will develop devices based on low-cost barocaloric materials and, due to the molecular characteristics, will progress towards challenging applications by exploring the limits of the smallest size of magnetic refrigerators. Academic and non-academic leaders, from top research institutions in Europe and outside, will expose the doctoral researchers to integrative, multidisciplinary, and multisectoral training in chemistry, materials science, physics, device development, and relevant transversal skills.
Duration: 01.2024-12.2027
- PERSEO
Title: European Training Network on PErsonalized Robotics as SErvice Oriented applications
PI: Prof. Dr. Friederike Eyssel
CITEC - CENTER FOR COGNITIVE INTERACTION TECHNOLOGY
Summary:
The personal robotics domain is raising new challenges concerning the need for robot behaviour with a high level of personalisation with respect to each user's needs and preferences. The aim is to have a cloud repository of robot behaviours that allows an easy personalised configuration approach. This requires the investigation of different robot capabilities to adequately understand and model the human-robot interaction and adapt the robot's behaviour to the context. The EU-funded PERSEO project will train early-stage researchers (ESRs) from the fields of computer science, philosophy, and psychology in how robotics technology can be personalised on the physical, cognitive and social levels. This will help the ESRs understand how to address social, legal and ethical issues that arise with the uptake of personal robots.
Duration: 01.2021-12.2024
- SPRING
Title: Doctoral Network for reSilience exPeRts IN future larGe-scale critical infrastructures
PI: Prof. Dr. Barbara Hammer
CITEC - CENTER FOR COGNITIVE INTERACTION TECHNOLOGY
Summary:
The project aims to develop an innovative research and training programme to prepare next generation experts in critical entities resilience design. Fifteen doctoral candidates will collectively engage in an ambitious interdisciplinary research project focusing on aspects related to the resilience design, real-time monitoring and control, anomaly detection and isolation, and incident response, in geographically distributed systems of cyber-physical systems. The PhD topics will investigate open research questions about the use of systems and control theory, formal methods, explainable AI, data-driven approaches, and human-centered design to build safe and resilient societal-scale critical entities. The project will also promote industrial excellence by offering opportunities to the researchers for testing their tools and frameworks in real-world scenarios, provided by the industrial partners. In this line, industrial partners will provide scenarios focusing on water, energy and transportation services, inspired by a real deployment using state-of-the-art and innovative IoT components. The research outcomes that will be validated in the context of these use cases will be reusable with other critical entities in other sectors.
Duration: 01.03.2026 - 28.02.2030
- Transcend
Title: Transcending limitations of translational research on Multiple Sclerosis and Autism Spectrum Disorder - Spectral, brain-related disorder, patient outcomes, cognition, effect, symptoms
PI: Prof. Dr. Lara Keuck
Faculty of Medicine OWL
Summary:
TRANSCEND brings together expertise in biomedical, computational, behavioural, clinical, epidemiological and philosophical research to advance translational research in medicine. TRANSCEND aims to add to the chronological and epistemic order of research from bench to bedside to practice with a more networked-based understanding of translation. This is particularly important in translational research on complex and chronic neurological conditions where the few low-hanging fruits of reductionist approaches seem to have been picked. TRANSCEND involves nine interlinked laboratories from clinical, biomedical, metamethodological, and philosophical sub-projects, which focus on autism spectrum disorder and multiple sclerosis. These conditions are characterised by an interconnected set of physical, cognitive and psychological symptoms, and unknown underlying disease mechanisms. While healthcare has been moving away from a purely single-cause view of medicine towards interconnected concepts of positive health, such a more complicated and nuanced notion of health and dis/ability is unintegrated within biomedical research. Most research designs are not well-suited to consider patient-relevant outcomes, the biological and social complexity of these conditions, and their implications in real-world healthcare settings, because their epistemology is oriented towards purification and reduction concerning research questions, disease models, and experiments. TRANSCEND proposes an integrative approach to translational research that embraces instead of reduces the complexity and diversity of the biological, clinical and social manifestations of the diagnoses. It will provide an innovative, interdisciplinary training along four research objectives to overcome key limitations of translational research on complex, chronic conditions: (1) making animal models more translational; (2) focusing on patient outcomes and scoping “disease” categories; (3) rethinking theragnostic strategies.
Duration: tba
Staff Exchanges as Coordinating Institution
Peace and Mobilities
The research programme aims to develop a new concept of peace that goes beyond the mere absence of violence, based on the experiences of people on the move. It fills a research gap by examining the role these people play in the construction of peace and the violence they experience both on their way and in supposedly peaceful societies. The aim is to extend studies on peace and violence to understand how both are mobilised.
Research and Innovation Staff Exchange (RISE) as a partner
- PANGAIA
Title: Pan-genome Graph Algorithms and Data Integration
PI: Prof. Dr. Jens Stoye
CeBiTec - Center for Biotechnology
Abstract:
Modern sequencing technology produces genome sequence data on a gigantic scale reaching into exabytes. The emerging urgent question is how these volumes of data could be arranged and analysed in a computationally efficient and biomedically meaningful manner. This EU-funded project is going to explore graph-based representation of large genome datasets and determine their advantages over traditional sequence-based presentation of pan-genomic data. Genomes that are evolutionarily close vary only a little and graph-based pan-genomic representation allows to remove redundancies while highlighting important differences. The research is going to demonstrate the advantage of the shift to the new data representation approach using comparative analysis, compression, integration and exploitation of genome data as the fundamental point
Duration: 01.2020-06.2025
Postdoctoral Fellowships
UCoCo
Stacking single-layer materials on top of the other enable the creation of materials with unique electrical and optical properties. The interlayer coupling – the interaction between the neighbouring atomic layers – is the key to the rich properties of the stacked layered materials. Recent studies have shown that the interlayer coupling can be modulated with an out-of-plane electric field on the atomic layers. Funded by the Marie Skłodowska-Curie Actions programme, the UCoCo project aims to investigate mechanisms that control the interlayer coupling in the ultrafast time scale using an out-of-plane terahertz electric field. The proposed approach could facilitate studies on the ultrafast control of quantum phases in various layered materials. It could also be applied as optoelectronic and all-optical ultrafast switches.
MONOWAX
Wax esters (WEs) are neutral lipids of major industrial importance, used as components of lubricants, pharmaceuticals, and cosmetics. Their production is based on chemical processes, which utilize mainly petroleum-derived feedstocks and generate hazardous waste. With diminishing fossil reserves, demand for industrial raw materials, and predicted effects of global warming, alternative bio-based platforms for the production of WEs are needed.
The MONOWAX project aims to explore the alternative production of WEs using a promising oleaginous microalgae Monoraphidium neglectum. Within the project, a vector toolkit for efficient gene expression in M. neglectum will also be developed. The outcome of this project will be a valuable contribution to the future development of new environment-friendly strategies to produce WEs.