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La red temática BIOSTATNET quiere ser el núcleo de conexión de los investigadores españoles de Bioestadística, con un enfoque flexible, abierto, integrador e interdisciplinar. Esta Red, pionera en España, consta de 8 nodos y 224 miembros liderados por estadísticos universitarios con proyectos propios de investigación, experiencia docente en bioestadística y colaboración estrecha con investigadores biomédicos. BIOSTATNET agrupa y representa las distintas líneas de investigación de cada uno de los nodos involucrados. Sus objetivos principales son:

  • Coordinar la investigación y la docencia de bioestadística en España, permitiendo su proyección internacional;
  • Potenciar la formación adecuada en bioestadística;
  • Favorecer su transferencia y aplicabilidad en biomedicina.

Noticias y Actividades

Job offer: Biostatistician
Savana is looking for a Biostatistician to play a key and exciting role in our fast-growing company, serving Spanish, English, German and French speaking markets. Based in our headquarters in Madrid, will participate on the challenging project of expanding Savana worldwide as well as serving our home market, Spain.   Deadline for applications: May 2019   They offer: Work with a multidisciplinary team of clinicians, computer engineers, computational linguists, mathematicians, designers, medical Natural Language Processing expert programmers and other disciplines. We are a team of professionals with a common goal: to blend the knowledge of all of us to seek excellence in our purpose. Coming from very different disciplines, we want everyone to learn from everyone, creating a unique entity that moves towards the transformation of health through Artificial Intelligence. An opportunity to provoke a positive impact. We seek to improve health on the planet through technology and to help people and health institutions. Our employees and collaborators strive to provide our users with the necessary tools and support to achieve a more accessible and egalitarian global health. We care about our environment and we are willing to improve it. An environment to express yourself as you are and enjoy what you know. We defend individuality to form a richer and more plural "ecosystem". Be yourself and tell us what you have learned and how could we use it together to help us achieve our purpose. If you like what you do, we like to work with you. Competitive salary conditions, flexible culture and a development framework to growth your career. People are our main asset, so we invest in training and development and recognize and compensate for achievements and valuable work. We trust in the talent and commitment of people and focus on objectives and results, so we are flexible in our way of working, providing a framework to reconcile our personal and professional lives.   Requirements: Fluent in English and Spanish. Degree in Statistics More than 2 years’ experience in Biostatistics. Capable of programming in R software is a must. Experience working in Clinical Research Understanding on technology, big data and AI applications in health. Excellent communication skills (verbal and written). Post-graduate degree in Biostatistics is a plus Strong foundation in coding skills relevant to statistics: R, SQL, WinBUGs, Python, etc Capable of contributing to the development of study design, the protocol and the Statistical Analysis Plan (SAP) Capable of participating in Study database design and programming Capable of analyzing data inconsistencies Experience developing of result tables, listing and figures according to SAP Experience on interpretation and presentation of clinical research results Interested on shaping the future of health, focussing on unmet medical needs. Ability to work well within a team or alone. Ability to work in a multinational, multidisciplinary and fast-growing environment. Maintain one's own strategy but adapting it to a changing and even volatile environment. Patient, flexible attitude, ability to perform under pressure. Autonomy, creativity, good capacities for analysis and organisation of work.   Contact:  
València International Bayesian Analysis Summer School
The Third edition of the València International Bayesian Summer School (VIBASS3) will take place from the 22th to the 26th of July 2019 in València (Spain). VIBASS3 is a 5-day summer school that offers an opportunity to be introduced into Bayesian learning without previous knowledge in the subject.   The five days of VIBASS are organised in three parts:   1) The first two days include a basic course on Bayesian learning (12 hours), with conceptual session and practical sessions with R packages. It would be advisable that participants bring their laptops for the practical sessions.   2) The second part is dedicated to an issue of current interest in Bayesian research.This edition is dedicated to Applied Bayesian Computation and the NIMBLE Platform for Hierarchical Modeling and MCMC. This 12 h course is provided by Daniel Turek, Assistant Professor of Statistics, Williams College and member of the NIMBLE Development Team.   3) Friday 29 is the last day of the school. It is devoted to the Third VIBASS Workshop. We will have two plenary sessions with invited speakers: Eleni Matechou (University of Kent) and Gonzalo García-Donato (Universidad Castilla-La Mancha). Attendants to the school are encouraged to present their research in an informal brainstorming as well as in a poster session.   VIBASS3 is organised by the VABAR research group and supported by Universitat de València and Biomathematics and Statistics Scotland, BIOSS.   More info in:
Summer school on advanced Bayesian methods
The Interuniversity Institute for Biostatistics and statistical Bioinformatics organizes for the third time a summer school on Bayesian methods. During one week, two courses will be taught on specific topics in Bayesian methodology. The focus is on Bayesian methods that are relevant for the applied statistician. Special attention will be devoted to novel statistical methodology. In the third edition of the summer school, the following two courses will be organized in Leuven from 23 to 27 September 2019: Two-day course (23-24 September) on Advanced Simulation and Numerical Methods for Bayesian Statistics by Dr. Mark Girolami (Imperial College, London and The Alan Turing Institute, UK) Three-day course (25-27 September) on Bayesian Variable Selection Methods by Dr. Ioannis Nzouftras (Athens University of Economics and Business, Greece) The target audience of summer school are statisticians and/or epidemiologists with a sound background in statistics, but also with background in Bayesian methodology. In both courses, practical sessions are organized, so participants are asked to bring along their laptop with the appropriate software (to be announced) pre-installed.   More info in:



Investigador Responsable: Carmen María Cadarso Suárez

Con 58 miembros liderados por Carmen Cadarso, Javier Roca, José A. Vilar y Francisco Gude investigando en: Inferencia en Modelos Aditivos Generalizados (GAM). Extensiones del Modelo GAM. Modelos Aditivos Multi-estado (MSM) en Supervivencia.


Investigador Responsable: Guadalupe Gómez Melis

El nodo Catalunya-Bio, liderado por Guadalupe Gómez Melis, está formado por 34 investigadores de cuatro universidades catalanas, tres universidades extranjeras y siete instituciones biomédicas. Sus principales líneas de investigación son de las áreas de la bioestadística y de la bioinformática.


Investigador Responsable: Pere Puig Casado

Con 18 miembros liderados por Pere Puig investigando en: modelización estadística avanzada, series temporales, datos longitudinales, curvas ROC, análisis de supervivencia y modelos mixtos.


Investigador Responsable: Carmen Armero Cervera

El Grupo Valencian Bayesian Research Group, VABAR, está formado por 24 investigadores cuyo objetivo es la implantación y desarrollo de metodologías novedosas de estadística espacial y temporal en escenarios reales de tipo epidemiológico, farmacológico y medioambiental.


Investigador Responsable: María Luz Durbán Reguera

Con 27 miembros liderados por María Luz Durbán Reguera, investigando en: Modelos basados en P-splines para datos espacio-temporales, Estimación y predicción en áreas pequeñas mediante P-splines, Métodos de estimación para curvas ROC.


Investigador Responsable: Antonio Martín Andrés

Con 10 miembros dirigidos por los catedráticos Antonio Martín Andrés y Juan de Dios Luna del Castillo, investigando en métodos tanto exactos como asintóticos para el análisis de Tablas de Contingencia


Investigador Responsable: Jesús López Fidalgo

El nodo Castilla-La Mancha – OED está formado por un total de 25 investigadores de 8 Universidades Españolas distintas y 1 extranjera. El Diseño Óptimo de Experimentos, que proporciona herramientas para una investigación más eficiente, es el punto de unión de los trabajos de estos investigadores.


Investigador Responsable: Vicente Núñez Antón

Con 27 miembros liderados por Vicente Núñez Antón investigando en: datos longitudinales, análisis de supervivencia, técnicas no paramétricas, modelización de la calidad de vida relacionada con la salud.