Other 2 PhD studentships for A.Y. 2023/24 will be available at the University of Bologna for candidates interested in any area of Statistical Sciences (start of activities: November 1st, 2023). The studentships are funded by NRRP ex D.M. 117/23 and ex D.M. 118/23; they are all linked to the development of the PhD projects illustrated below.
All available positions will be covered by a scholarship. The award will be for three years, subject to satisfactory progress.
Special Topics Scholarships
Grant ex D.M. 118/23: SPATIAL MODELLING APPROACHES TO CLIMATE FINANCE AND SUSTAINABLE TRANSITION GOALS
PI: Silvia Romagnoli
The main topic of the grant is in line with the objectives of supporting the digital and ecological transition of the economic system and the administrative apparatus, with an expected impact on effectiveness and efficiency. Environmental impact assessment is at the centre of proper management and adaptation/mitigation policies necessary to achieve the objectives set by regulators. It is precisely in this context that the use of innovative strategies is linked to methodological and data innovation that can allow a distinction of the spatial location of the analysis and prepare targeted actions to highlight the major criticalities. Satellite data allows for objective and geographically localized analysis that promotes, on one hand, the valorization of the resource in question, and on the other hand, the determination of local risks related to natural variables and climate change, with an impact on the entire economic pattern, from the productive sector to the financial and the administrative one. The identification of risk-hedging solutions is among the objectives of mitigation and adaptation in which the spatial dimension plays a fundamental role given the nature of the problem itself.
References
- G. Christakos, “Spatiotemporal Random Fields: Theory and Application”, Elsevier, 2017 (second edition)
- F.E. Benth-J.S. Benth, “Modeling and Pricing in Financial Markets for Weather Derivatives”, World Scientific, 2013
Grant ex D.M. 118/23: Development of computational medical technologies and data analysis for the prevention, diagnosis, and treatment of neuromuscular and musculoskeletal diseases
PI: Saverio Ranciati
The general objective of the research is to identify the epidemiological and organizational characteristics that determine the outcomes of surgical interventions such as the implantation of bone joint prostheses. By developing the main methods related to survival analysis, including the estimation of risk and survival functions, the estimation of the effects of the covariates through the application of the Cox regression model and the estimation of a model with frailty effects, we will mainly investigate the outcomes of hip surgery. Hip surgeries are resource-intensive operations, among the most frequently performed on the elderly, with an increasing volume trend in recent years due to the aging of the population. Taking different perspectives, the aim of the research is to investigate how to improve the allocation of healthcare resources and the efficiency of services for this type of treatment, conditioned by the results obtained from the application of avant-garde statistical methodologies for processing the available information.
The empirical analysis will start with detailed information on the pre-operative conditions of the patients and from validated post-operative outcome indicators, for a more reliable measurement of the effectiveness of the interventions, also monitoring of the different types of prosthesis, also in relation to the patient's clinic, therapy and risk factors.
Following the indications of the World Health Organization (WHO) which has recently defined the centrality of the patient as one of the fundamental dimensions that define the quality of care, statistical methodologies will be evaluated to better analyze the data obtained with the PROMs collection in patients undergoing elective surgery of the hip, knee and shoulder at the Rizzoli Orthopedic Institute of Bologna following the model implemented by other national registries, where data on functional outcomes and quality of life reported by patients are already collected. The centrality of the patient is reflected in the detection of functional outcomes and quality of life reported by patients, called Patient-reported Outcomes (PROMs).
The impact of the results of this analysis lies in the possibility of providing useful ideas for the development of clinical/surgical choices that are efficient both in terms of the use of resources and in terms of outcomes.
From a statistical point of view, the goal is to identify the state of the art in the scientific literature for the type of analysis being treated, assess the potential of each method and identify the most suitable for the purpose. If theoretical gaps or improvements should be highlighted, it will be of great interest to integrate what is known with the contribution of the doctoral student, with a view to actual academic research activity.
Applicants may be of any age or citizenship, and must have a 2nd cycle degree or a single cycle degree from an Italian university or an equivalent qualification from other countries of at least four years' duration.
For courses that will start in the next academic year, the call for applications will be published at the page https://www.unibo.it/[…]/how-to-apply-phd-programme. The application must be submitted following the online procedure that will be linked in the call.
Applicants can also apply to the selection for the admission to the International PhD College of the Institute of Advanced Studies (ISA). See the page http://www.isa.unibo.it/en/activities/PhD_ISA for details. ISA PhD fellow will be offered free accommodation.
Admission is governed by a competition that allocates scholarships on the basis of comparative merit. Comparative assessment is made by the Boards of Examiners, appointed according to the University regulations, that evaluates qualifications and interviews candidates. After the selection process has been completed, the Board of Examiners draws up a merit list. Scholarships are allocated according to the ranking established in the merit list.
Qualifications include: undergraduate and/or master degrees transcripts of records, curriculum, scientific publications, GRE and TOEFL (if available), awards, grants, and one letter of recommendation.
The interview is meant to allow the committee to determine if the candidate is a good fit and if he/she has the motivation and drive to complete a doctorate. Moreover, it covers the technical background of each candidate. Technical questions are on the level, for instance, of:
- Exercise 7.6, 7.8, 8.3, 8,7 Casella Berger
- Exercise 7.4, 7.21, 8.2, 9.1 Mood, Graybill, Boes
Candidates are allowed to work on their answers with pencil and paper. They should then explain their answers to the examiners and answer additional follow-up questions.
In the event of positions linked to special topics, questions linked to the topic of interest might also be raised by the examiners on top of those above described. Candidates are invited to carefully read the topics, and, in case of interest, contact the PI's before the interview takes place.
Suggested readings for the interview:
- Casella, G., & Berger, R. L. (2002). Statistical inference (Vol. 2). Pacific Grove, CA: Duxbury.
- Mood A. Graybill F.A., Boes D.C. (1974): Introduction to the Theory of Statistics, McGraw Hill College.
The interview takes place on a date announced after the results of the evaluation of qualifications.
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For more information, contact phd.stat@unibo.it
E-mail monica.chiogna2@unibo.it
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