Description of the 40th cycle scholarships (2024-2027)

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1 Title: Artificial Intelligence for coastal ocean modelling
Description: Despite decades of research, no single deterministic prediction scheme accurately forecasts processes like wave runup and coastal currents. This challenge makes coastal modeling and engineering a promising area for approaches based on Artificial Intelligence (AI). This project aims to explore advanced AI-based modeling techniques using training and testing data from both deterministic models and observations.
Contact: Lorenzo Mentaschi (lorenzo.mentaschi@unibo.it)

2 Title: Physics of the Solid Earth: all aspects of solid earth geophysics, such as seismology, physics of volcanism, geodesy, geodynamics, tsunami
Description: As the title indicates, the topic is not fixed a priori. It will be adapted based on the profile of the selected candidate. All profiles in solid earth geophysics are welcome, and particularly those based on seismology, volcanology, and related hazards.
Contact: Silvia Castellaro (silvia.castellaro@unibo.it)

3 Title: Geophysical methods for stratigraphic exploration purposes: new frontiers
Description: This Ph.D. program aims at exploring, studying, improving and applying new or emergent geophysical exploration methods. These can include, as an example, distribute acoustic sensing (DAS) or 2D-3D single station seismic approaches
Contact: Silvia Castellaro (silvia.castellaro@unibo.it)

4 Title: Physics-informed machine learning for medium to long range ocean forecasting
Description: This PhD research explores physics-informed machine learning (PIML) to improve medium to long-range (weeks to years) ocean forecasting. PIML models will integrate ocean physics with machine learning's ability to capture complex patterns in vast datasets. This research aims to improve forecasting accuracy, efficiency, and interpretability, ultimately leading to better predictions and understanding of relevant ocean phenomena at different spatial and temporal scales. 
Contact: Paolo Oddo (paolo.oddo@unibo.it)

5 Title: Modelling of limb radiative transfer in presence of scattering layers: the CASIA project
Description: The Physics of the Atmosphere Group has a consolidated line of research in radiative transfer modelling in atmosphere at terrestrial and solar wavelengths. Below the supervision of Prof. T. Maestri, the successful candidate will investigate the optical properties of high Troposphere low Stratosphere scattering layers and work on a definition of fast algorithm to solve the radiative transfer equation at limb in presence of multiple scattering. The research is in the frame of the activities of the “CASIA CAIRT: Analisi e Sinergia con IASI-NG” project funded by the italian space agency (ACCORDO ATTUATIVO n. 2023-3-HB.0) and in collaboration with CNR and Univ. of Basilicata. The use of field campaign data from nadir and from limb instrumentations is foreseen for the testing of the developed tools.
Contact: Tiziano Maestri (tiziano.maestri@unibo.it)

6 Title: Coupled data assimilation of far infrared measurements to improve subseasonal to seasonal predictions
Description: The new ESA mission FORUM will make it possible for the first time to observe the Earth on the far infrared area of the emission spectrum. Exploiting this new set of data is of paramount importance, yet much remains to be understood on the amount of information they contain, let alone on the mathematical and physical approaches to extract desired atmospheric fields. MC-Forum is a project funded by the Italian Space Agency (ASI) aimed at studying the potential of the Far Infrared data for improving medium-range and subseasonal-to-seasonal climate prediction. MC_Forum will work in tandem with its peer ASI project Fit_FORUM, based at UNIBO, devoted to developing inverse method to extract physical relevant quantities from the observed radiances.

The aim of the PhD project is to study the impact of FORUM measurements to improve the estimation of initial conditions and of some parameters of both atmospheric models and coupled ocean-atmosphere models. The activity of this PhD position focuses on the use of ensemble assimilation methods, and the study will rely on idealized contexts with models of low or medium complexity. The goal is to answer basic methodological questions otherwise precluded in more complex and more computationally expensive models. 

The candidate will work with a modelling suite that includes the atmospheric model of intermediate complexity SPEEDY, its coupled ocean version SPEEDY-NEMO the atmospheric-ocean spectral model MAOOAM. She/He will have the opportunity to use DA software package such as the Python DAPPER (github.com /nansencenter/DAPPER) or Fortran palatiform PDAF (pdaf.awi.de/trac/wiki). The candidate will perform a sensitivity study of DA to the spatio-temporal density of measurements, in relation to different time horizons and an assessment of the benefits deriving from the use of FORUM-like measures. Depending on the results and on the specific interest of the student, we will consider hybrid DA and machine learning algorithm to enhance the capability to exploit the data information content.

Contact: Alberto Carrassi (alberto.carrassi@unibo.it); Paolo Ruggieri (paolo.ruggieri2@unibo.it)

7 Title: Smart and sustainable exploitation and management of the coastal and the ocean resources, in a changing climate
Description: The PhD will deal with managing the availability and exploitation of resource potential in the seas and ocean coasts for blue growth. The candidate will use open-source codes and tools for the simulation of waves, currents, sediment transport and water quality and the interaction processes between marine forcings and the environment. AI potentials in coastal engineering will be investigated.
Contact: renata.archetti@unibo.it

8 Title: Development of climate services for nature-based adaptation strategies to climate change
Description: Science-based evidence of effectiveness of nature-based solutions (NBS) as climate adaptation approaches is still confined to pilot interventions, especially in Africa, and their efficacy in future climate scenarios is largely unknown. At the same time benefits and drawbacks of different nature-based adaptation strategies must be weighted with respect to competing interests and needs in different economic sectors, socio-economic and ecological impacts, and sustainable development goals, in order to identify low/no regret climate adaptation strategies.

The overall aim of this PhD project will be the development of innovative climate services enabling evaluations of the effectiveness of NBS in specific contexts of Sub-Saharan Africa. Existing datasets of global and regional climate projections will be exploited to force statistical and dynamical sectoral models, along with national level finer resolution climate projections and observations for validation and bias correction. The successful candidate will cooperate with several international research teams, within the framework of the Horizon Europe research and innovation project ALBATROSS (grant agreement No 101137895). More information on ALBATROSS project here: https://albatross-project.eu/

Contact: Laura Leo (laurasandra.leo@unibo.it); Silvana Di Sabatino (silvana.disabatino@unibo.it); Paolo Ruggieri (paolo.ruggieri2@unibo.it)

9 Title: User centered approaches in shaping an experience-driven fruition of hospital environment -  Approcci user-centered per la definizione di soluzioni di fruizione experience-driven in ambiente ospedaliero.
Description: The research topic is closely grounded in the user centered perspective where users are placed at the core of the investigation process to analyze the current experience – from booking the health service, to concretely receiving it in the hospital structure – and possibly provide more efficient, suitable and satisfactory solutions. The cross-cutting nature of the investigation deals with both the definition of a user journey and at the same time with all the constraints and characteristics of a complex environment as a hospital campus is. The research activity involves the user experience from booking to taking charge of the patient and subsequent release considering actions, times, key players according to the following methodologies: Desk and field search; User Research (reference users); Benchmark and scenario analysis; stakeholder involvement; co-design of solutions; concept; prototyping; iteration. The scope is to redefine the user journey into a multiple physical and digital environment reflecting the complexity of services envisaged in the healthcare system while offering an easy-to-understand layout framework meeting the expectations, needs and requirements of UN SDGs 2, 3, 11. The successful candidate will work with Prof. J. Gaspari and his team.
Contact: Jacopo Gaspari (jacopo.gaspari@unibo.it)

10 Title: Livable and sustainable hospital spaces. Service-driven design strategies to facilitate accessibility and wayfinding in common areas in hospital structures
Description: The research topic is widely related to defining effective solutions for improving the quality and the livability in hospital structures which are nowadays affected by multiple and interrelated requirements due to the high level of complexity structurally informing the healthcare system. While the management activities have been largely investigated with reference to several disciplines, the connection between the management processes and the users’ experiences has received less attention by the scientific community. However, the increasing importance of providing livable, adequate and sustainable spaces compliant with UN SDGs 2, 3, 11 is calling for new strategies to place users at the core of design initiative to ensure all pavilions, services and places can be accessible, in a clear, easy and sustainable way. The conditions of use by users are investigated according to user-centered design methods, considering the different parameters and factors that can influence accessibility, comfort and autonomy. As regards the internal spaces, the in-depth analysis will cover the different scales of the design, including technological and digital aspects as enabling elements. The successful candidate will work with Prof. J. Gaspari and his team.
Contact: Jacopo Gaspari (jacopo.gaspari@unibo.it)

11 Title: Interaction of Urban Heat Island and Urban Pollution Island
Description: Urban Heat Island (UHI) and Urban Pollution Island (UPI) are two major problems of the urban environment and have become more serious with rapid urbanization. Yet, the  interaction of the Urban Heat Island and Urban Pollution Island is still not fully elucidated and debated, which limits also the planning of adequate mitigation strategies. The research will be devoted to the investigation of the interaction between UHI and UPI utilizing a combination of numerical modeling for pollutant dispersion and measurements from high resolution ad-hoc constructed networks of low-cost sensors. 
Contact: : Erika Brattich (erika.brattich@unibo.it); Silvana Di Sabatino (silvana.disabatino@unibo.it)

12 Title: Downscaling techniques at different temporal scales including long term
Description: The overarching goal of the project is to develop a methodology for downscaling at different temporal scales. Starting from near term the candidate will work on the development of high-resolution and skillful seasonal and decadal climate predictions for the extra-tropics. Both near term and long term will involve the testing using with numerical mesoscale models. The work will be conducted in the framework of active Horizon Europe research and innovation projects and will cooperate with various international research teams. The candidate will have access to state-of art numerical models and access to the computing facilities of the Atmospheric Physics group.
Contact: Silvana Di Sabatino (silvana.disabatino@unibo.it); Paolo Ruggieri (paolo.ruggieri2@unibo.it)

13 Title: Generative AIPowered Collaborative Coastal Monitoring
Description: The Artificial Intelligence (AI) is no longer just a futuristic vision. It has become a tangible reality deeply transforming research, industrial and commercial sectors. In this context, generative AI emerges as a driving force, transcending the confines of academia and specialized laboratories to permeate every corner of society. However, its transformative potential in monitoring and managing coastal areas remains unexplored. This project aims to explore how generative AI can be harnessed to protect our coasts and their precious ecosystems, actively engaging humans in this critical mission.

To achieve this goal, a deep understanding of how generative AI works and when to use it is paramount in developing innovative strategies for coastal protection. By fostering a comprehensive theoretical and practical grasp of AI, this project aims to pinpoint the opportunities offered by this technology and devise fresh approaches for coastal areas preservation. It would be fascinating to explore the opportunities arising from the development of collaborative man-machine monitoring tools, which combine human intelligence with the advanced capabilities of Artificial Intelligence (AI). These tools could leverage the potential of machine learning, empowering capabilities of data analysis, and advanced sensing technology to significantly enhance the monitoring and protection of coastal areas. This approach promises to yield significant and sustainable innovations, fostering a harmonious relationship between humanity and the environment.

In conclusion, this project aims to provide a lucid and pragmatic insight into the application of generative AI for coastal protection, thereby making a substantial contribution to the research and conservation of our precious natural heritage.

Contact: Giovanni Coppini (giovanni.coppini@cmcc.it)

14 Title: Data-Driven Coastal Natural Disaster Prediction and Mitigation
Description:  This PhD scholarship focuses on enhancing the prediction and mitigation strategies for natural disasters in coastal regions through data-driven methodologies. Leveraging advanced computational models and data analytics, the research aims to integrate diverse data sets including historical weather, oceanographic, hrydrological data, and socio-economic information to develop more accurate and timely predictions of coastal hazards such as storm surges.

The project will explore the use of machine learning algorithms, satellite and insitu observations and simulation models to interpret complex data and predict the impact of climate variables on coastal resilience. By analyzing trends and patterns from extensive datasets, the scholarship seeks to improve early warning systems and disaster preparedness plans, ultimately contributing to safer and more resilient coastal communities. The research will also involve the development of new tools for real-time data collection and analysis, incorporating remote sensing and IoT technologies to monitor coastal environments continuously. Collaborations with local governments and international bodies will be key to implementing and testing the effectiveness of prediction models and mitigation strategies in real-world settings.

The outcomes of this research are expected to significantly contribute to the field of coastal disaster management by providing actionable insights and advanced tools for risk assessment. This scholarship aligns with global efforts to enhance ocean science capabilities as outlined in the United Nations Decade of Ocean Science for Sustainable Development, supporting the broader goals of sustainable coastal management and human safety.

Contact: Giovanni Coppini (giovanni.coppini@cmcc.it)

15 Title: Communities and Citizen Science for Global Coastal Ocean Monitoring
Description:  Coastal areas are characterized by infrastructures and uses that can have negative effects on natural resources and habitats of high ecological importance; added to all this are the impacts of climate change, such as the increase in the frequency of extreme events. In this context, observations are fundamental, as they allow you to monitor different parameters and acquire data in space and time, allowing you to control any variation and anomaly and support numerical models that require as many data as possible to be validated. For this reason it is necessary to use innovative and even autonomous technologies that allow the study of coastal processes and dynamics at different spatial and temporal scales, in different oceanographic and meteorological conditions. The development of advanced and low-cost technologies is essential to increase observation capacity for monitoring marine ecosystems and studying potential impacts induced by human activities and climate change. Activities will include: support for the development of oceanographic sensors and measurement instruments, testing and installation at pilot sites; support for programming (python) of the tools to be developed; processing of acquired data for the study of coastal processes; study and application of quality control procedures and techniques to the acquired data; support for data sharing in the main portals (Emodnet Copernicus); support for the intercalibration of instruments with reference systems; demonstration of the scientific importance of these types of sensors to address key coastal scientific challenges.
Contact: Viviana Piermattei (viviana.piermattei@cmcc.it)

16 Title: Innovative approaches for a sustainable and just water governance
Description: This PhD Program invites proposals for doctoral research projects addressing the multifaceted challenges within the realm of water governance and sustainable development. This call aims to delve into critical issues concerning just transition and governance, co-designed decision support tools, stakeholder network analysis, water trade-offs across various sectors, water resources evaluation and monitoring.

Background: Climate change materializes also through its changes in the water resources worldwide. Globally, the urgent issues of water scarcity and quality deterioration underscore the need for innovative strategies in water governance and management. Tackling these challenges demands interdisciplinary approaches, integrating scientific, technological, and institutional elements within the same governance framework. Consequently, governance emerges as a crucial determinant in evaluating the effectiveness of management strategies and policy implementations, especially in the context of socio-economic assessment and stakeholder engagement within the water sector and its role for ecosystems' preservation.
PhD Research Proposal can be developed along the following topics:

• Water Governance 4.0: Research projects should explore new potential governance frameworks seeking to harmonize water issues on a transnational or international scale accounting for climate change impacts on water resources. Central to this exploration is the quest for new governance models that bolster the interface between climate science and policy in water governance. These frameworks must prioritize just governance, ensuring equity and efficiency in water use while addressing inequalities in access. Assessing the significance and efficacy of such collaborative endeavors in tackling water challenges is crucial for informing future policy and action.
• Participatory approaches for new water governance frameworks: Research projects should focus on developing novel governance frameworks that foster inclusivity and stakeholder engagement in water management processes. Special attention should be given to the co-design of goals and solutions through collaborative platforms, such as "living laboratories," to enhance policy adaptation and enforcement and stakeholder network analysis to assess and enhance stakeholder participation in water management.
• Enhancement of Socio-economic Indicators for M&E in the water sector: Research projects can explore the integration of socio-economic indicators for water resources and climate change adaptation. The development of robust indicators can contribute to improved monitoring, enforcement, and evaluation of regulatory and policy actions.

Methodological Approach: Proposals should outline a clear methodological approach that integrates qualitative and quantitative methods, as appropriate, to address the research objectives. Interdisciplinary methodologies are encouraged to facilitate comprehensive analyses of complex water governance issues. This scholarship is funded by the CMCC Foundation (Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici), Information Systems for Climate Science and Decision-making Division located among Milano, Bologna and Lecce.

Contact: Giulia Galluccio (giulia.galluccio@cmcc.it)

17 Title: Enabling Transition and Transformation in Coastal Areas
Description: This PhD Program invites proposals for doctoral research projects addressing the multifaceted challenges within the realm of adaptation governance and finance in coastal areas. This call aims to delve into critical issues concerning just transition and transformation, co-designed decision support tools, stakeholder network analysis, funding and investment opportunities for coastal resilience.

Background: Europe is the fastest-warming continent in the world. Extreme heat, once relatively rare, is becoming more frequent while precipitation patterns are changing (EEA, 2024). As the global climate changes, rising sea levels, combined with high tides, storms and flooding, put coastal and island communities, assets and vital resources increasingly at risk (IPCC, 2022).

Today, less than 10% of all climate finance is allocated to adaptation (CPI 2023). The global adaptation financing gap is widening, and current levels of funding remain well below the estimated USD 212 billion per year needed through to 2030 in developing countries alone (WHO 2023).

PhD Research Proposal can be developed along the following topics:

• Coastal governance 4.0: research projects should explore new potential governance frameworks that bolster the interface between climate science and policy towards climate resilience in coastal areas. These should foster inclusivity and stakeholder engagement, being centered on the “just transition” principles, thus ensuring equity and at the same time addressing underlying inequalities.
• Adaptation finance for coastal resilience: research proposals should contribute to fill in the adaptation finance gap and to identify innovative mechanisms to unlock funding and investment opportunities for coastal resilience. Special attention should be given to the identification of key enabling factors, co-benefits and potential barriers, as well as on the exploration on innovative mechanisms to embed coastal resilience into financial decision-making and to underpin the potential of these climate related challenges as investable asset classes.

Methodological Approach: Proposals should outline a clear methodological approach that integrates qualitative and quantitative methods, as appropriate, to address the research objectives. Interdisciplinary methodologies are encouraged to facilitate comprehensive analyses of complex governance and finance issues.

This scholarship is funded by the CMCC Foundation (Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici), Information Systems for Climate Science and Decision-making Division located among Milano, Bologna and Lecce.

Contact: Giulia Galluccio (giulia.galluccio@cmcc.it)

18 Title: High-resolution Ensemble Ocean Forecasting and Data Assimilation at Coastal scale
Description:  This PhD scholarship focuses on advancing the precision and reliability of ocean forecasting in coastal regions through high-resolution ensemble models and sophisticated data assimilation techniques. The scholarship aims to develop forecasting models that can predict complex coastal dynamics and ocean-atmosphere interactions more accurately. These models will integrate diverse data sets, including satellite observations, in-situ measurements, and hydrological data, to enhance the resolution and predictability of coastal weather events, sea states, and ecosystem health. The research will involve optimizing data assimilation methods to improve the integration between observational data and model forecasts. This will enable better management of coastal resources, nature based solution planning, hazard prevention, and response to climate variability. The scholar will also explore innovative approaches to model coupling and ensemble forecasting to address the challenges posed by the fine-scale processes that dominate coastal zones. Collaborations with leading oceanographic institutions and use of state-of-the-art computational facilities are expected to form the cornerstone of this initiative.

Contact: ivan.federico@cmcc.it

19 Title: Integrate groundwaters and marine waters in a seamless modelling of a catchment-sea continuum
Description: This PhD scholarship aims to develop advanced integrated models for the comprehensive assessment and management of water resources across hydrological basins and coastal-marine zones. The research focuses on bridging the modeling gap between surface water, groundwater, and marine systems to better understand the cumulative impacts of environmental changes and human activities. The scholar will work on integrating the scientific and technical knowledge from hydrological modeling with coastal ocean and estuarine dynamics modeling approaches to simulate the multi-physics and multi-scales  processes and feedback mechanisms among different water bodies. A water modeling system of a catchment-sea continuum selected within the Mediterranean Sea will be implemented by using a new generation unstructured-grid ocean model with time dependent vertical coordinates following the free surface and with wetting-drying capability, i.e. SHYFEM MPI ZSTAR code (Micaletto et al; 2022, Verri et al 2023). The expected innovation is to solve the water budget at the groundlevel by including the infiltration process, and the feedback mechanism at the land-sea interface.
Contact: Giorgia Verri (giorgia.verri@cmcc.it)

20 Title: Improving Seasonal Forecast of Extreme Precipitation
Description: Extreme precipitation is one of the most impactful weather-related hazards in terms of economic impact, number of disasters and loss of lives.  
A reliable forecasts of such kind of extremes can reduce the weather impact on our society. This is true for different time horizons, and we’ll focus here on the seasonal forecast. First, reanalysis and general circulation model output will be used to define  and tailor the most reliable drivers of extreme precipitation over different locations. Then, purely Data Driven and hybrid Data-Driven Dynamical Forecast Systems will be used to improve our ability to forecast extreme precipitation on the seasonal time horizon, with a special focus over Europe. As an example, the characterisation of the relationship between extreme precipitation over Europe and the integrated vapour transport crossing the western European boundary,  will lead to the definition of the most appropriate, eventually hybrid, forecast model, to be compared to standard Dynamical Forecast Systems.
Contact: enrico.scoccimarro@cmcc.it

21 Title: Improving Regional Ocean Short- Term Forecasting: Optimizations and Innovations
Description: Improvements in short-term marine forecasts represent a crucial challenge for numerous sectors, including navigation, fishing, tourism, marine resource management, and the prediction of extreme events. It is essential to develop accurate forecasts of marine conditions to ensure the safety and efficiency of operations at sea. In recent years, significant progress has been made thanks to optimizations and technological innovations that have revolutionized the field of weather-marine forecasting. One of the main optimizations concerns the use of increasingly sophisticated and high-resolution numerical models, which integrate data from various observational sources. These data, released with increasing temporal and spatial frequency, represent a continuous challenge for integration into oceanographic models. Furthermore, the implementation of machine learning algorithms can further enhance the models' ability to predict extreme events, providing sufficient warning to adopt effective preventive measures. Another methodology to achieve more accurate and reliable forecasts is based on ensemble forecasting, an approach that combines multiple simulations to produce a set of forecasts that provide an assessment of uncertainty. This method, based on performing numerous parallel forecasts with perturbations in initial conditions, boundary conditions, or model parameters, allows for a probabilistic representation of future events, improving the accuracy of forecasts and the management of risks associated with marine conditions.
Contact: Emanuela Clementi (emanuela.clementi@cmcc.it)