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The thematic network BIOSTATNET aims to link together Spanish researchers in biostatistics with an integrative, multidisciplinary, flexible, and open focus.
This is a pioneer network in Spain mainly consisting of 8 nodes leaded by statisticians from different universities with own research projects and teaching experience in biostatistical matters and working closely with biomedical researchers. BIOSTATNET gathers and represents the main lines of investigation of each of the nodes involved. Its main objectives are:

  • Coordinate research and teaching of biostatistics in Spain, allowing for an international projection;
  • Promote an adequate education in biostatistics;
  • Help to show its transparency and applicability in biomedicine.

News and Activities

PhD Position
A 3-year scholarship is offered to develop new statistical methods applied to Biodosimetry, in the PhD program in Mathematics at the Universitat Autònoma de Barcelona (UAB).   It is a multidisciplinary project between the UAB and the Institut de Radioprotection et de Sûreté Nucléaire (IRSN). The selected person would spend 50% of the period at the UAB and 50% at the IRSN, obtaining the doctorate with "international mention".   If you are interested, please send your CV to P. Puig ( or to Sophie Ancelet (   More info: PhD_project_UAB_IRSN
PhD position in statistical ecology. Lille, France.
a PhD position in statistical ecology is available at the Evo-Eco-Paleo lab (Lille, France), starting October 2019. We already posted the position on several lists a few months ago, but we have had very few responses so far. The new deadline for answering is May 20th. The following advertisement is in English and French. Please spread the word and sorry for cross-posting. Cheers, François Massol **** Assessment of plant-pollinator networks via metabarcoding approaches: evaluation, comparison with classic approaches and optimization to propose a next-generation biomonitoring protocol   Location: Unité Evolution, Ecologie & Paléontologie (EEP), CNRS UMR 8198, Université de Lille, Bâtiment SN2, F-59655 Villeneuve d’Ascq cedex, France   Theme: In a recently published opinion (Bohan et al., 2017, Trends in Ecology & Evolution, 32, 477-487), the implementation of next-generation biological monitoring approaches has been proposed as a cost-effective tool to detect ecosystem changes accurately and generically at a global scale in the next decade. With such an approach, Next-Generation Sequencing (NGS) of DNA would provide the relative abundances of operational taxonomic units or ecological functions in the various environments of the planet Earth. Machine-learning methods would then be used to reconstruct ecological networks of interactions from these raw data from NGSs and relate them to different environmental parameters in order to detect and predict changes in ecosystems. As part of the ANR project “Next Generation Biomonitoring of change in ecosystems structure and function” (ANR NGB, principal investigator: David Bohan, INRA Dijon; coordinator for the University of Lille: François Massol), we seek to develop and test protocols based on NGS approaches to predict the structure of ecological interaction networks and hence the quality of the functioning of ecosystems and the services that depend on them.   The thesis proposed aims more particularly at developing inferential approaches on plant-pollinator networks, in continuation of studies conducted at the Evo-Eco-Paléo laboratory (ANR ARSENIC 2014-2018 and Climibio project on plant-pollinator networks in the Lille metropolis). The student’s work will consist in analyzing metabarcoding data obtained on pollen carried by previously captured insects (two capture methods were used: active capture using insect nets and passive capture using attractive pan traps), developing learning methods for reconstructing interaction networks using machine learning from molecular data, evaluating their efficiency compared to conventional methods, by comparing the networks obtained using conventional vs. NGS approaches, using the data thus obtained to assess structural differences between urban and semi-rural plant-pollinator networks, as well as the exploitation of native and non-native floral resources by pollinators in urban areas, issuing recommendations for management and monitoring structures of natural areas concerning the use of such protocols to qualify the proper functioning of terrestrial ecosystems. The traditional capture data (hand nets and pan traps) have already been collected, and the NGS data on the sites of the Lille metropolitan area will be obtained in 2019, around the beginning of the thesis.   The work of the PhD student will be fully integrated into the dynamics of the NGB project, which will naturally lead him to collaborate with the different partners of the project, both for the development of methodological and statistical aspects (UMR MIA, AgroParisTech-INRA Paris and Imperial College, London) or the reflection on molecular techniques and bioinformatics (UMR BioGeCo, INRA Bordeaux), but also in the framework of regular meetings allowing the other three PhD students of the project (Dijon, Paris, Rennes) to discuss their respective topics and share their experience learning molecular data networks.   Key words: bioinformatics; machine learning; network reconstruction and analysis; next-generation sequencing   PhD supervisors: François Massol (, DR CNRS, UMR8204 CIIL and UMR8198 EEP, Lille Nina Hautekèete (, PR University of Lille, UMR8198 EEP, Lille Céline Poux (, MCF University of Lille, UMR8198 EEP, Lille   Other local collaborators: Anne Duputié, MCF University of Lille, UMR8198 EEP, Lille Yves Piquot, MCF University of Lille, UMR8198 EEP, Lille Anne-Catherine Holl, Technician University of Lille, UMR8198 EEP, Lille Cécile Godé, Assistant engineer CNRS, UMR8198 EEP, Lille Sophie Gallina, Research engineer CNRS, UMR8198 EEP, Lille   Funding: funding for the work to be performed is already acquired (ANR NGB) half of the PhD studentship is already obtained (ANR NGB) the other half of the studentship will be asked from the doctoral school SMRE (   Profile: We are looking for a highly motivated candidate having a primary interest in applied statistics and ecology. The ideal candidate will also have good capacities for bioinformatics and/or experience in ecological/evolutionary data analyses, especially dealing ecological networks. Prior experience with molecular ecology techniques (metabarcoding in particular) will be appreciated. Finally, the candidate should have obtained good marks and ranking at the master’s degree.   Because of the project’s interdisciplinary nature, we are open to applicants from ecology/evolution, statistics, computer science and related areas.   Interested applicants should have a look at and for information about the project and the laboratory.   Contact: Please send your application to François Massol ( and Céline Poux ( This should include (1) a detailed CV, (2) a cover letter putting forward relevant training, (3) a copy of grades and rank for both the master degree (first and second-year marks), (4) name and contact information of two reference persons. We recommend that you send your application as soon as possible and by no later than May 20th 2019. Review of applications will begin immediately and continue until the position has been filled.   Starting date: October 2019  
Oferta de empleo
OFERTA DE CONTRATO DE TITULADO SUPERIOR   PROYECTO: Diseño Óptimo de Experimentos Aplicado a la Industria Agroalimentaria, Farmacéutica y Metalmecánica financiado por el la Consejería de Educación, Cultura y Deportes de la Junta de Comunidad de Castilla-La Mancha.   Requisitos: Diplomatura y/o licenciatura/grado y/o máster y/o doctorado. Preferencia en Estadística, Matemáticas o cualquier otra con base estadística sólida. Objetivo general: Realización de tareas de colaboración en el proyecto de investigación. Duración de contrato: Un año (desde el 15 de junio de 2019 hasta el 15 de junio del 2020). Plazo: Desde la publicación de la convocatoria, hasta el día 20 Mayo 2019. Solicitudes: Quienes deseen tomar parte en esta convocatoria deberán presentar solicitud electrónicamente, cumplimentando el modelo disponible en la página de internet, de acceso público, de la Universidad de Castilla-La Mancha:, o accediendo directamente desde la página principal de la Universidad ( ) ,INVESTIGACIÓN, CONVOCATORIAS, CONVOCATORIAS DE PERSONAL CON CARGO A PROYECTOS DE INVESTIGACIÓN. Ref.: 2019-COB-9325 Lugar de trabajo: Grupo de investigación Diseño Óptimo de Experimentos en el campus tecnológico “Fábrica de Armas” de Toledo. Contacto: Los candidatos interesados pueden contactar con Dr. Raúl Martín Martín (    Más información: CONVOCATORIA 2019-COB-9325



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

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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.