{"id":480,"date":"2024-01-06T16:50:31","date_gmt":"2024-01-06T15:50:31","guid":{"rendered":"https:\/\/datascience.unifi.it\/eccellenzadisia\/?page_id=480"},"modified":"2025-07-11T16:02:50","modified_gmt":"2025-07-11T14:02:50","slug":"graduate-programs","status":"publish","type":"page","link":"https:\/\/datascience.unifi.it\/eccellenzadisia\/graduate-programs\/","title":{"rendered":"Graduate programs"},"content":{"rendered":"<div class=\"gb-container gb-container-6db4e4e1\" id=\"master-programs\">\n\n<h2 class=\"gb-headline gb-headline-5f01fdb9 gb-headline-text\">Master programs for data scientists<\/h2>\n\n\n\n<p>In addition to the master&#8217;s degrees in <a href=\"https:\/\/www.sds.unifi.it\/\" target=\"_blank\" rel=\"noreferrer noopener\">Statistics and Data Science<\/a>, <a href=\"https:\/\/www.informaticamagistrale.unifi.it\/\" target=\"_blank\" rel=\"noreferrer noopener\">Computer Science<\/a>, <a href=\"https:\/\/www.dsts.unifi.it\/\" target=\"_blank\" rel=\"noreferrer noopener\">Design of sustainable tourism systems<\/a>, and<a data-type=\"link\" data-id=\"https:\/\/www.sst.unifi.it\/\" href=\"https:\/\/www.sst.unifi.it\/\" target=\"_blank\" rel=\"noreferrer noopener\"> Software: Science and Technology<\/a>, we have recently activated the master&#8217;s <a data-type=\"link\" data-id=\"https:\/\/www.datascience-cs-ia.unifi.it\/index.html?newlang=eng\" href=\"https:\/\/www.datascience-cs-ia.unifi.it\/index.html?newlang=eng\" target=\"_blank\" rel=\"noreferrer noopener\">degree in Data Science, Scientific Computing &amp; Artificial Intelligence.<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Data Science, Scientific Computing &amp; Artificial Intelligence<\/h3>\n\n\n\n<p><strong>Scientific Coordinator<\/strong>: Prof.ssa Donatella Merlini<\/p>\n\n\n\n<p><strong>Other DiSIA members<\/strong>: Michele Boreale, Daniele Castellana, Anna Gottard, Monia Lupparelli, Andrea Marino, Alessandra Mattei, Maria Cecilia Verri<\/p>\n\n\n\n<p><strong>Network<\/strong>: Lead department: Statistica, Informatica, Applicazioni &#8220;G. Parenti&#8221; (DISIA). Co-lead department: Chimica &#8220;Ugo Schiff&#8221; (DICUS), Biologia (BIO), Fisica e Astronomia, Matematica e Informatica &#8220;Ulisse Dini&#8221; (DIMAI)\u00a0 e Scienze della Terra (DST) dell\u2019Universit\u00e0 di Firenze.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Learning objectives<\/h3>\n\n\n\n<p class=\"has-drop-cap\">The Master&#8217;s Degree Course in Data Science, Scientific Computing &amp; Artificial Intelligence intends to provide a degree course in a certainly emerging sector such as that of data science and scientific computing. In fact, the profession of Data Scientist is naturally emerging as one of the most sought professions on the market and the demand significantly exceeds the actual availability of these figures. The course of study therefore has the objective of training professional figures capable of answering research questions arising from the pervasive presence of complex data, both structured and unstructured, and of high dimensionality (so-called big data) in the most varied fields of application; in particular, in scientific fields of an interdisciplinary nature involving biology, chemistry, physics, and geology.<\/p>\n\n\n\n<p>This objective is achieved through the acquisition of solid theoretical and practical skills in various fields of computer science, mathematics and statistics and their application through various paths declined in the various scientific fields, including those of in-depth study of computer science and mathematics for data science, scientific computing and artificial intelligence.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Structure of the course of study<\/h3>\n\n\n\n<p>The Degree Course is divided into 2 years for a total of 120 credits (ECTS) and normally the student&#8217;s activity corresponds to the achievement of 60 CFU per year. The following types of training activities are foreseen:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>27 CFU of mathematical-statistical training;<\/li>\n\n\n\n<li>27 CFU of computer science training;<\/li>\n\n\n\n<li>6 CFU&nbsp;of&nbsp; legal-linguistic training;<\/li>\n\n\n\n<li>18 CFU of training in various scientific disciplines;<\/li>\n\n\n\n<li>18 CFU self-chosen by the student;<\/li>\n\n\n\n<li>24 CFU for the final exam and further training activities.<\/li>\n<\/ul>\n\n\n\n<p>In order to enhance the heterogeneity of incoming students, the study program offers diversified&nbsp; activities of typology caratterizzante and a wide range of activities of typology affine on emerging Data Science topics. This makes it possible to offer students, also according to their own interests, a wide choice and deepening of knowledge and skills on emerging scientific topics. In particular, some courses in computer science, mathematics and statistics of typology caratterizzante, foreseen in the first year, must be chosen by the student on the basis of their knowledge and skills. Also in the first year, some courses are compulsory for all students. The same consideration applies to a set of courses of typology affine chosen by the student, which can always be selected according to the knowledge and skills required.<\/p>\n\n\n\n<p>The training activities of typology affine combine mathematics, statistics and information technology skills with disciplinary fields such as those of biology, chemistry, physics and geology (for example, biology and computational chemistry; the predictive methods of structural biology,&nbsp; statistical phisics, physics of complex systems and modern geology; methods for the analysis of biological, geological with spatial characterization and for environmental chemistry data, and of images in the various fields of physics). Furthermore, the activities of typology affine broaden the mathematical, statistical and computer science skills in specific methodological and applicative fields of support to Data Science.<\/p>\n\n\n\n<p>Furthermore, in various courses there will be projects and laboratory activities that will allow students to deal directly with the most advanced Data Science tools and with the resolution of concrete problems. As regards the educational activities chosen individually by the student, courses of typology <em>caratterizzante<\/em> and <em>affine <\/em>not previously chosen or other courses activated in the University may be selected. The choice of these activities is free as long as it is consistent with the training project.<\/p>\n\n\n\n<p>The courses will be held in Italian, except for some optional courses which will be in English. The activities planned over the 2 years, with the related teaching load, are described on the web page of the Master (available at: <a href=\"https:\/\/www.datascience-cs-ia.unifi.it\/\">https:\/\/www.datascience-cs-ia.unifi.it\/<\/a> )<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Career opportunities<\/h3>\n\n\n\n<p class=\"has-drop-cap\">Graduates in Data Science, Scientific Calculation &amp; Artificial Intelligence will possess the skills to directly address public administrations,&nbsp; companies and laboratories that are active in sectors such as the management of large databases and the collection, processing and analysis of large amounts of data, especially in the fields of biology, chemistry, physics and geology, as well as the production of data through numerical simulations.<\/p>\n\n\n\n<p>In particular, two main occupational and professional outlets can be identified:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>the first, an expert in systems and methodologies for data management, security, modeling and analysis, corresponding to courses that include more advanced level courses and in-depth study of information technology and mathematics for data science and scientific computing;<\/li>\n\n\n\n<li>second, an expert in the production and processing of scientific data, corresponding to courses that especially study scientific applications in biology, chemistry, physics and geology.<\/li>\n<\/ul>\n\n\n\n<p>Given the enormous interest in scientific research in the sector, obviously both from university and from the most advanced industries, the degree course will try to favor the brightest minds by encouraging them to continue with third-level studies.<\/p>\n\n\n\n<p>More info: <a href=\"https:\/\/www.datascience-cs-ia.unifi.it\/\">https:\/\/www.datascience-cs-ia.unifi.it\/<\/a><\/p>\n\n<\/div>\n\n<div class=\"gb-container gb-container-32f1b6d7\" id=\"phd-programs\">\n\n<h2 class=\"gb-headline gb-headline-312bc9d9 gb-headline-text\">PHD programs for Data scientists<\/h2>\n\n\n\n<p>Furthermore, along with the Ph.D. in Statistics (part of<a href=\"https:\/\/www.phdmatinfstat.unifi.it\/\"> Ph.D. program in Mathematics, Computer Science, Statistics<\/a> of the University of Florence) for which this project will provide funding for three 3-year scholarships, we have recently activated the Ph.D. program in \u201cLife Course Research\u201d<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Ph.D. Scholarships &#8211; Ph.D. in &#8220;Mathematics, Computer Science, Statistics&#8221;<\/h3>\n\n\n\n<p class=\"gb-headline gb-headline-fe135700 gb-headline-text\"><strong>Xuanye Dai<\/strong> &#8211; Rethinking Data Science (tutor Prof. <a href=\"https:\/\/cercachi.unifi.it\/p-doc2-0-0-A-3f2a3d31332728.html\">A. Gottard<\/a>) &#8211; Cycle XXXIX 2023-2026<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Ph.D. in \u201cLife Course Research\u201d<\/h3>\n\n\n\n<p><br><strong>Scientific Coordinator<\/strong>: Prof. <a href=\"https:\/\/danielevignoli.com\/\">Daniele Vignoli<\/a><\/p>\n\n\n\n<p><strong>Other DiSIA members<\/strong>: <a href=\"https:\/\/www.unifi.it\/p-doc2-0-0-A-3f2c342938302c.html\">Raffaele Guetto<\/a> (Coordinator of the Socio-Demographic curriculum), <a href=\"https:\/\/www.unifi.it\/p-doc2-0-0-A-3f2b3a2e3a302f.html\">Elena Pirani<\/a>, <a href=\"https:\/\/www.unifi.it\/p-doc2-0-0-A-3f2a3c31392b2d.html\">Gustavo De Santis<\/a>.<\/p>\n\n\n\n<p><strong>Network<\/strong>: Universit\u00e0 di Firenze (coordinating University), Universit\u00e0 di Bari, Libera Universit\u00e0 di Bolzano, Universit\u00e0 di Cagliari, Universit\u00e0 della Calabria, Universit\u00e0 di Catania, Universit\u00e0 Milano-Bicocca, Universit\u00e0 del Molise, Universit\u00e0 di Napoli Federico Secondo, Universit\u00e0 di Padova, Universit\u00e0 del Piemonte Orientale, Universit\u00e0 Politecnica delle Marche, Universit\u00e0 di Roma Campus Biomedico, Universit\u00e0 di Palermo, Universit\u00e0 di Pisa, Universit\u00e0 di Roma Sapienza, Universit\u00e0 di Sassari, Universit\u00e0 di Torino, IRCCS Don Gnocchi, Universit\u00e0 di Ferrara, Universit\u00e0 Vita-Salute San Raffaele, Universit\u00e0 di Roma Tor Vergata, Andrological Sciences Onlus, Scuola Sant\u2019Anna di Pisa, Universit\u00e0 di Siena, Universit\u00e0 di Bologna, Universit\u00e0 di Salerno, Scuola Normale Superiore di Pisa, Universit\u00e0 di Modena e Reggio Emilia, Universit\u00e0 di Messina, Universit\u00e0 Ca\u2019 Foscari di Venezia.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Brief description of the Ph.D.<\/h3>\n\n\n\n<p class=\"has-drop-cap\">The life of humans, from conception to death, unfolds along a path that traverses the perinatal period, infancy, adolescence, adulthood, and eventually old age. This progression has often led to a segmented study of life stages throughout the course of ages. <strong>Biomedical disciplines<\/strong> have dissected this journey by examining changes in vital processes and the varying predisposition to diseases. <strong>Developmental psychology and social psychology<\/strong> have identified developmental stages from infancy to old age, describing the trajectories and mechanisms that account for shifts in behavior and its neurobiological substrates, elucidating pathways of resilience and vulnerability. <strong>Demography<\/strong> has determined age-specific mortality probabilities from birth, accounting for various differential aspects. Moreover, it has quantitatively described family and reproductive dynamics and how generations of children succeed those of their parents. <strong>Sociology <\/strong>has investigated the interrelationships between life course events and the economic and social context.<\/p>\n\n\n\n<p>The overarching theoretical framework that allows the integration of these disciplinary traditions into a unified foundational perspective is the <strong>life course approach<\/strong>, employing a bio-psychosocial perspective. The life course perspective enables the organic study of how events that mark individuals&#8217; lives in their main phases of growth, maturation, and decline manifest and change over time and space, as well as how these events interconnect individual biographies.<\/p>\n\n\n\n<p>The<strong> Ph.D. program<\/strong> in<strong>&nbsp;Life Course Research<\/strong>&nbsp;fosters the study of life courses and the significant events that shape them from a<strong>&nbsp;holistic and transdisciplinary perspective.<\/strong> The program establishes an alliance among scholars from the&nbsp;<strong>biomedical, psychological, and socio-demographic fields<\/strong>.<\/p>\n\n\n\n<p>The Ph.D. program in&nbsp;<strong>Life Course Research<\/strong>&nbsp;will train a new generation of highly skilled scholars relying on an&nbsp;<strong>evidence-based approach<\/strong>&nbsp;with a strong emphasis on&nbsp;<strong>quantitative methods and data analysis<\/strong>.<\/p>\n\n\n\n<p><strong>Unique features<\/strong>&nbsp;of the Ph.D. program in Life Course Research:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Thematic<\/strong>&nbsp;rather than disciplinary identity<\/li>\n\n\n\n<li><strong>Super-departmental<\/strong>&nbsp;and&nbsp;<strong>super-regional<\/strong>&nbsp;nature of the Consortium to overcome the fragmentation of local approaches&nbsp;<\/li>\n\n\n\n<li><strong>Multilevel teaching<\/strong> <strong>structure<\/strong>&nbsp;fueled by a large Scientific Consortium of <strong>29&nbsp;associated universities<\/strong> across all Italian areas<\/li>\n<\/ul>\n\n\n\n<p>More info: <a href=\"https:\/\/www.phd-lcr.com\/\">https:\/\/www.phd-lcr.com\/<\/a><\/p>\n\n<\/div>","protected":false},"excerpt":{"rendered":"<p>Master programs for data scientists In addition to the master&#8217;s degrees in Statistics and Data Science, Computer Science, Design of sustainable tourism systems, and Software: Science and Technology, we have recently activated the master&#8217;s degree &#8230; <a title=\"Graduate programs\" class=\"read-more\" href=\"https:\/\/datascience.unifi.it\/eccellenzadisia\/graduate-programs\/\" aria-label=\"Read more about Graduate programs\">Read<\/a><\/p>\n","protected":false},"author":3,"featured_media":786,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"ngg_post_thumbnail":0,"footnotes":""},"class_list":{"0":"post-480","1":"page","2":"type-page","3":"status-publish","4":"has-post-thumbnail","6":"no-featured-image-padding"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Graduate programs - Rethinking Data Science<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datascience.unifi.it\/eccellenzadisia\/graduate-programs\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Graduate programs - Rethinking Data Science\" \/>\n<meta property=\"og:description\" content=\"Master programs for data scientists In addition to the master&#8217;s degrees in Statistics and Data Science, Computer Science, Design of sustainable tourism systems, and Software: Science and Technology, we have recently activated the master&#8217;s degree ... 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