On June 10 there will be the opening of the Florence Center of Data Science, an inter-departmental research center that mainly involves statisticians, mathematicians, computer scientists, engineers and economists.
For the inauguration there will be a workshop with interesting interventions. The poster with the program is attached.
We at SIB have welcomed the invitation of many international scientific societies to celebrate women’s day in mathematics, identified with May 12 (https://may12.womeninmaths.org/).
In particular, SIB organized on May 10th, an event that focuses not only on the contribution of women in biostatistics research but also on biostatistics in research for women’s health. You’re all invited.
The flyer with all the details can be downloaded here:
10 maggio a Torino presso la sala Principi D’Acaja del rettorato
dell’università di Torino, l’Italian Biostatistics Group (IBIG), una società di
statistici farmaceutici italiani e membro italiano della EFSPI (https://www.efspi.org/), organizza la prima
edizione dell’”Italian Bayesian Day for Clinical Research”. Si dibatterà di
aspetti classici e innovativi della metodologia bayesiana applicata allo
sviluppo clinico. Relatori provenienti dall’accademia e dall’industria
proporranno diverse prospettive sull’impiego della statistica bayesiana, ancora
poco utilizzata nel contesto della ricerca clinica.
attenzione sarà rivolta al ruolo della statistica bayesiana nei processi
decisionali, dalla determinazione della dimensione campionaria, all’analisi dei
dati, alla pianificazione degli studi clinici. L’evento sarà tenuto in
Per ulteriori informazioni e
modalità di registrazione: https://simef.it/index.php?option=com_eventbooking&view=event&id=478&catid=7&Itemid=386&lang=it
Ci sono limitate possibilità di finanziamento per la
partecipazione di studenti.
Sarà emesso a breve (entro fine giugno) un bando per un assegno di ricerca nel settore statistico per un periodo di un anno – rinnovabile – per un’attività di ricerca da svolgersi presso il CUSSB (Unisr-Milano).
L’obiettivo della ricerca è quello di sviluppare tecniche di data-integration per la modellizzazione di dati di diversa natura, elettrofisiologici, neurofisiologici, scale psicometriche, nella valutazione delle emozioni. In particolare, si andrà a studiare la struttura di dipendenza tra risposta soggettiva, risposta oggettiva psicofisiologica e le misure di efficacia associate a messaggi visivi (da media/social media) a forte valenza emotiva per valutarne l’ impatto informativo.
Il contesto di applicazione va dalla valutazione delle campagne in Sanità al social marketing piu’ in generale. Il progetto coinvolgerà candidati particolarmente motivati a lavorare in un contesto multidisciplinare (statistica, biomedicina, psicologia, bioingegneria).
Il bando è indirizzato a giovani in possesso di un dottorato di ricerca (in materie statistico-quantitative) con competenze nell’ambito di network possibilmente anche in contesti tempo-varianti. In attesa dell’emissione del Bando Ufficiale invito tutti gli interessati ad inviare il loro curriculum già da ora alla mia attenzione (email@example.com).
Network inference for modeling complex systems is becoming a central theme in biology and disease. However, network inference is a fast evolving aspect of data science in biological and biomedical research. The objective of this EMBO Workshop is to bring together experts from different disciplines to present and discuss their latest findings in using network inference and network integration for modeling the complexity of biological systems at the molecular dynamic and genetic levels. The workshop will facilitate trans-disciplinary interactions around new approaches and current biological and biomedical questions and showcase frontier research in network inference and biology.
More information can be found here:
Dr. Linda Valeri in the Department of Biostatistics at Columbia University Mailman School of Public Health is seeking a Postdoctoral Research Fellow. The position is available immediately. The one-year position can be extended to additionally two years on the basis of performance, evaluated at the end of each year. This position will provide the opportunity to carry out causal inference research in either or both of two collaborative avenues:
- The investigation of environmental mixtures health effects in the context of Bangladeshi and American perinatal and adult intergenerational cohorts in collaboration with the Department of Environmental Health Sciences at Columbia University and Harvard University.
- The analysis of mobile passive (GPS, call/text logs, sleep data) and active (surveys) data streams in collaboration with the New York Psychiatric Institute, NY, the Departments of Psychiatry at Columbia University and Harvard University, and McLean Hospital.
The broad goal of the successful candidate will be the development and application of blended causal inference and machine learning approaches and automated software tools. The approaches will be applied to harness exposomic data and mobile health data to investigate the joint causal effects of environmental and behavioral factors over time to inform policy on environmental mixtures and to discover behavioral targets of treatment in psychosis. The postdoctoral fellow will have the opportunity to collaborate with scientists across fields and across domestic and international research institutions.
The 2019 edition of the Summer School on Modern Methods in Biostatistics and Epidemiology will be held from June 2 to June 15, 2019 at Castelbrando, in Cison di Valmarino, Treviso, Italy.
The Summer School provides many introductory and advanced courses in medical statistics and epidemiology, and their application to etiology research and public health. Courses last one week (except for the Stata courses, held on Sunday, which last one day). Students can attend for one day, one week, or two weeks.
Instructors come from Harvard University and from several European institutions, including Karolinska Institutet, Leicester University, London School of Hygine and Tropical Medicine, Bocconi University and University of Milano-Bicocca.
Discounted rates are available to students, to returning or multiple participants, and to members of the IBS and of SISMEC. Early bird rates apply until March 24th, 2019. Discounts can be applied only after the registration fee is paid (on the remaining tuition amount).
IBS members have a 20% discount on the tuition fee.
For additional information and to apply please refer to: www.biostatepi.org
A course on advanced regression topics in modelling survival data is offered by the University of Milano – Bicocca on October 29-30, 2018. The course is given by Dott. Federico Rotolo (Innate Pharma, FR) at the School of Medicine, Via Cadore 48, Monza (https://www.medicina.unimib.it/it/dipartimento/come-raggiungerci).
The course is free, but if you would like to attend, please send an e-mail to firstname.lastname@example.org
First Day: Frailty Models (FM)
Motivating examples, Univariate vs Shared FMs, Parametric FMs, Semiparametric FMs , Research topics, Practical session with R
Second Day: Lasso Penalization
Penalized likelihood, The role of the tuning parameter, Cross-validation, Beyond the lasso penalty, Research topics, Practical session with R
PhD Program in Public Health, University of Milano – Bicocca
School of Medicine, University of Milano – Bicocca
Competing Risks and Multistate models are widely used in medical research when survival data involve composite outcomes with absorbing events (competing risks) and possible intermediate events (multistate). These models can be used to obtain risk prediction on future outcome development and to assess the prognostic impact of patient characteristics and therapeutic interventions on the outcome development.
Prediction – The incidence function is generalized to competing risks data by its decomposition into absolute risks of each absorbing event. Absolute risks are called “crude probabilities” emphasizing the indirect protection that each absorbing event determines on the others. In the presence of multistate data, the intermediate events are included in the absolute risks which are called “state probabilities”, emphasizing that subjects may sojourn in intermediate states in the multistate process that takes to the absorbing events.
Prognostic Impact – The hazard function is generalized to competing risks data by its decomposition into cause specific hazard of each absorbing event. In the presence of multistate data, the intermediate events are included among the hazard functions that are called “transition hazard” between the states, to emphasize the motion among the intermediate and absorbing states.
The course will deal first with the clinical questions and corresponding theoretical quantities. This link will be crucial to guide the student in the approach to estimation and inference to be adopted.
Syllabus available at https://elearning.unimib.it/course/info.php?id=22057
To enroll please write to Laura Antolini email@example.com
Host Organization: University of Milano Bicocca, School of Medicine – Monza via Cadore 48
Following the success of the “Networking Biostatistics” joint conference hold in Milano last April, we are promoting a special session on “Networking biostatistics and bioinformatics” at CIBB (Computational Intelligence methods for Bioinformatics and Biostatistics) conference, which is an International conference on biostatistics, bioinformatics, systems and synthetic biology and medical informatics.
This year the Conference will take place in Portugal (6-8 September) at the Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal.
The goal of the session is to encourage a “data driven” approach aimed at developing appropriate models that provide new insights into the biomedical problem. Since, in the big data era, the biomedical data turns out to be complex and multivariate, robust and computationally efficient statistical tools are needed to investigate complex dependecies within data structure.
In this spirit, the special session will be devoted to both theoretical advances and applications of statistical methods for the analysis of high-dimensional genetic/omics data. Topics of interest include, but are not limited to:
• Expert Systems and Bayesian Networks
• Graphical models
• Multivariate techniques for dimensionality reduction
• Latent class (mixed) modelling
We hope the CIBB conference matches your scientific interests.
More detail on the conference and the scientific topics of the conference, are available at the conference website http://eventos.fct.unl.pt/cibb2018.