Consulter les offres d’emploi

Lecturer / Senior Lecturer Position in Statistics at Massey University
Publiée le 13/03/2019 14:45.
CDI, Palmerston North, New Zealand.
Entreprise/Organisme :Massey University
Niveau d'études :Doctorat
Description :Applications are invited for a Lecturer/Senior Lecturer in Statistics within the School of Fundamental Sciences in the College of Sciences at Massey University (New Zealand). The School of Fundamental Sciences is a multi-disciplinary research and teaching unit within the College of Sciences at Massey University, Palmerston North. It incorporates groups in Biochemistry and Genetics; Plant and Microbial Sciences; Chemistry and Biophysics; Mathematics and Mathematical Physics; Statistics and Bioinformatics; and Computer Science and Information Technology. You will be expected to pursue independent research. You will develop collaborations across the University and beyond with researchers in other subjects; make a significant contribution to the School’s research outputs; attract research grants; and teach at any level as may be required. Existing research interests of the Statistics and Bioinformatics Group include network tomography; smoothing methods; spatial statistics; statistical genetics; statistical geophysics; statistical quality control; and statistics in epidemiology and medicine. For further information see https://masseyunicareers.nga.net.nz/cp/index.cfm?event=jobs.checkJobDetailsNewApplication&returnToEvent=jobs.listJobs&jobid=B1EFE3EC-1BCA-6392-6746-AD158DC4D346&CurATC=EXT&CurBID=62AFB35D-9273-4A11-8DCC-9DB401354197&JobListID=22FC4F47-E994-46A3-B8C9-9BC901269F43&jobsListKey=268ce81f-3b79-4614-8018-40ecdb76eae9&persistVariables=CurATC,CurBID,JobListID,jobsListKey,JobID&lid=26415900056 Enquiries of an academic nature should be directed to either Professor Martin Hazelton (Head of the School of Fundamental Sciences, Tel: +64-6-9517642; Email: m.hazelton@massey.ac.nz) or Professor Mark Bebbington (Head of the Statistics and Bioinformatics Group, Tel: +64-6-9517641; Email: m.bebbington@massey.ac.nz).
En savoir plus :https://masseyunicareers.nga.net.nz/cp/index.cfm?event=jobs.checkJobDetailsNewApplication&returnToEv
Contact :m.hazelton@massey.ac.nz
Assessing the interplay between bacterial and host genetics on human infectious diseases
Publiée le 19/02/2019 10:31.
Référence : Human-bacteria genetics.
CDD, Institut Pasteur, Paris 15.
Entreprise/Organisme :Institut Pasteur
Niveau d'études :Doctorat
Date de début :April 2019 at the earliest
Durée du contrat :2 ans
Rémunération :Depending on experience
Secteur d'activité :Academic research
Description :CONTEXT & OBJECTIVES Applications are invited for a two years postdoctoral fellowship at the Institut Pasteur within the Statistical Genetics group in the Center of Bioinformatics, Biostatistics and Integrative Biology (C3BI). The genetics of common human diseases has been extensively, and successfully, explored using the now popular GWAS (genome-wide association study) approach, an agnostic and systematic screening for association between genetic variants and phenotype. In recent years, the same principle has been applied to other predictors and outcome data (e.g. PHEWAS for Phenome-wide association studies, EWAS for Epigenome-wide association study). With increasing genetic data on human pathogens, the community is showing strong interest for the implementation of similar approaches to study the impact of bacterial genetics on human phenotypes, and the interplay between host and bacteria genetics. In collaboration with other research group at the Institut Pasteur, our group is developing methodologies to address these questions using some of the largest and richest dataset available to date with extended genetic, phenotypic and environmental data. The work will address multiple statistical and computational challenges, and the population structure across bacterial strains in particular. The selected candidate will both lead method development and corresponding real data analyses. The project is highly collaborative, involving experts in statistics and computational sciences from our group and the C3BI (including over 100 biostatisticians and bioinformaticians), but also biologist and epidemiologist, as the functional impact of associated variants will be validated with genome editing (e.g., with Crisp-Cas9) in mice models, and with ex vivo assays in relevant human tissues. The selected candidate will be mentored by Dr. Hugues Aschard, but will also work with members of our research group and collaborators involved in the project. She/he will have access to all resources at Pasteur, including in particular the High Performance Computing Cluster which includes over 2,000 cores, and the rich scientific life of the campus (over 1,000 researchers from 11 departments on site). QUALIFICATIONS The position requires advance knowledge in statistics and computer sciences. The applicants should therefore have substantial educational background in Statistics/Biostatistics, Bioinformatics, Computer Science or other relevant disciplines. Experience with linear mixed model is required. ADDITIONAL INFORMATION Interested applicants should send their curriculum vitae, a brief cover letter, and contact information from at least one referee to Dr. Hugues Aschard (hugues.aschard@pasteur.fr). More information about our group and the C3BI can be found here https://research.pasteur.fr/en/team/statistical-genetics/ and here https://research.pasteur.fr/en/center/c3bi/.
En savoir plus :https://research.pasteur.fr/en/team/statistical-genetics/
Job.description_GWASbact.pdf
Contact :hugues.aschard@pasteur.fr
Poste de DATA MANAGER
Publiée le 13/02/2019 21:30.
Référence : Poste DM 01.
CDD, Montpellier.
Entreprise/Organisme :INSERM
Niveau d'études :DUT/Licence ou équivalent
Date de début :dès que possible
Durée du contrat :6 mois
Rémunération :grille hospitalière
Secteur d'activité :Recherche epidemiologique et clinique
Description :Le travail portera sur la mise en place des bases de données longitudinales. Le candidat devra assurer la qualité des données récoltées et la mise à disposition de ces données. Le travail consistera aussi à la mise en œuvre d’analyses statistiques dans le domaine de la neuropsychiatrie.
En savoir plus :https://www.inserm-neuropsychiatrie.fr/fr
Contact :sylvaine.artero@inserm.fr
Junior Sports Quantitative Analyst
Publiée le 16/11/2018 16:00.
Référence : SMARTODDS JUNIOR QUANT.
CDI, LONDON.
Entreprise/Organisme :SMARTODDS
Niveau d'études :DUT/Licence ou équivalent
Rémunération :20-50k£
Secteur d'activité :Sports betting
Description :As a quantitative analyst at Smartodds, you will be part of an exciting environment, predicting outcomes of professional sports on behalf of our clients. We focus on football, American football, baseball, basketball, cricket, golf, ice hockey, and tennis. The junior quant analyst will be part of the quant team and assist the senior quants in their work. This will consist in writing basic statistical analyses, developing Shiny applications and maintain/improve the existing code library. We expect the candidate to learn new concepts very fast and be passionate about the job, which mixes sport, betting, maths and computing together. If you think that you tick the following boxes then please apply. This is a fantastic opportunity to work in a relaxed environment on a topic you love. Education Essential: BSc in Maths/Stats/Computer science. Desirable: MSc or equivalent in one of the above Skills and Experience Essential Proficient in one of R/Python Good statistics knowledge. Fast learner. Fluent in English. A passion for sports, betting, stats or computing. Desirable: Knowledge of R Shiny framework/ html development. Knowledge of SQL. Knowledge of Linux operating system. Benefits Flexible working hours Competitive salary and discretionary bonus 30 days annual leave plus public holidays Generous pension scheme and education budget Casual dress code Freshly made lunch and dinner three days a week
En savoir plus :https://www.smartodds.co.uk/Careers/Vacancies
Contact :benoit.jottreau@smartodds.co.uk
Ingénieur Biostatistiques
Publiée le 05/11/2018 21:47.
CDD, SFR ICAT - UFR Santé - Angers.
Entreprise/Organisme :Université d'Angers
Niveau d'études :Master
Date de début :Janvier 2019
Durée du contrat :11 mois
Rémunération :Entre 2043 € et 2628,86 €
Secteur d'activité :Recherche Santé
Description :Le profil de poste est détaillé dans le document pdf joint. Il est également important de savoir qu'une prolongation de contrat est possible à l'issu de ces 11 mois.
En savoir plus :NA
FP_Ingé Biostatistiques_Santé_JR.pdf
Contact :jeremie.riou@univ-angers.fr
Phd in Statistics
Publiée le 01/11/2018 19:17.
Référence : EWI2018-74.
Thèse, Delft, Netherlands.
Entreprise/Organisme :TU Delft
Niveau d'études :Master
Sujet :Data science for injury prevention and performance improvement
Date de début :1 March 2019, flexible
Durée du contrat :4 years
Rémunération :€2266—€2897 per month
Secteur d'activité :Research
Description :Job Description The program “Citius, Altius, Sanius” aims to stimulate people of all performance levels to engage in physical activity through sports and fitness to improve their health and performance by providing informative and motivating information using advanced sensor and data science techniques. The program comprises six applied projects and three fundamental projects. For one of the fundamental projects, entitled “Data science for injury prevention and performance improvement” we are looking for a PhD candidate. “Data science for injury prevention and performance improvement” concentrates on providing a data-based tailored advice for health and performance. The PhD position is based within the Statistics Group of the Delft Institute of Applied Mathematics. In the research, a personalized model will be developed allowing to give tailor made advice to individual athletes. The research comprises both methodological research in statistics as well as research in the domain of sports engineering and will make contributions to both fields. Requirements The candidate possesses an MSc degree in mathematics (specialization statistics or probability theory) or a related discipline in which mathematics, statistics and/or machine learning forms a prominent part. Some experience with epidemiology, statistical modelling and handling / analysis of data sets is advantageous but not a necessary requirement. We require very good communication skills and fluently spoken and written English. The position includes modest teaching duties. Candidates are expected to finish their project with a PhD thesis, and disseminate the results through publications in peer-reviewed journals, and presentations at international conferences. 
En savoir plus :https://www.academictransfer.com/nl/50691/
Contact :j.soehl@tudelft.nl
Postdoctoral Research Fellow - Stochastic Simulation, Uncertainty Quantification, Statistical modeli
Publiée le 17/09/2018 08:51.
Référence : Postdoc - Chaire StressTest.
CDD, Palaiseau.
Entreprise/Organisme :Ecole Polytechnique, France
Niveau d'études :Doctorat
Date de début :dès que possible
Durée du contrat :3 ans
Rémunération :2400€ nets mensuels dépendant de l'expérience
Secteur d'activité :Stochastic Simulation, Uncertainty Quantification, Statistical modeling
Description :Location. École Polytechnique is a French public institution of higher education and research in Palaiseau, in the southwest of Paris. It was established in 1794 by the mathematician Gaspard Monge during the French Revolution. It is one of the most prestigious and selective French grandes écoles. Polytechnique has several research laboratories operating in various scientific fields (physics, mathematics, computer science, economics, chemistry, biology, etc.). Research program. The Chaire “Stress Testing” is a specific research program between Ecole Polytechnique and BNP Paribas, and is hosted at Polytechnique by the Center of Applied Mathematics https://portail.polytechnique.edu/cmap/en This research project is part of an in-depth reflection on the increasingly sophisticated issues surrounding stress tests (under the impulse of the upcoming European Banking regulation). Simulation of extreme adverse scenarios is an important topic to better understand which critical configurations can lead to financial and systemic crises. These scenarios may depend on complex phenomena, for which we partially lack information, making the modeling incomplete and uncertain. Last, the data are multivariate and reflect the dependency between driving variables. From the above observations, different lines of research are considered: 1) the generation of stress test and meta-modeling scenarios using machine learning 2) the quantification of uncertainties in risk metrics 3) modeling and estimation of multidimensional dependencies Keywords: Bayesian Networks, copulas, dependent data, Deep Learning, Gaussian processes, machine learning, Markov Chain Monte Carlo, meta-modeling, multivariate statistics, rare event simulation, risk metrics, splitting methods, stochastic algorithms, stochastic and Bayesian optimization, uncertainty propagation Candidate profile: • A PhD in Probability and Statistics, or equivalent • A proven track record in quality research, as evidenced by research publications in top scientific journals and conferences • Solid working knowledge of some of the topics listed above (see keywords) • An understanding of financial risks is desirable • Exposure to development of numerical methods or data analysis (with Python, R) is desirable Position: 3 years, extension is possible. Although this is mainly a research position, there is the possibility of a small teaching load Net salary: about 2400€/month depending on the experience How to Apply: Your application should include a Cover Letter, Resume, publications. With your application, we ask that you briefly outline your experience against the selection criteria in the position description. Contact for application: emmanuel.gobet@polytechnique.edu
En savoir plus :https://drive.google.com/file/d/1vPBXCjCTzHh447pvphxSPH2zihYlF90z
PostDocChaireStressTest.pdf
Contact :emmanuel.gobet@polytechnique.edu
Lecturer - Stochastic Simulation, Uncertainty Quantification, Statistical modeling
Publiée le 17/09/2018 08:51.
Référence : Lecturer - Chaire Stress Test.
CDD, Palaiseau.
Entreprise/Organisme :Ecole Polytechnique, France
Niveau d'études :Doctorat
Date de début :Dès que possible
Durée du contrat :3 ans
Rémunération :2800€ net mensuel en fonction de l'expérience
Secteur d'activité :Stochastic Simulation, Uncertainty Quantification, Statistical modeling
Description :Location. École Polytechnique is a French public institution of higher education and research in Palaiseau, in the southwest of Paris. It was established in 1794 by the mathematician Gaspard Monge during the French Revolution. It is one of the most prestigious and selective French grandes écoles. Polytechnique has several research laboratories operating in various scientific fields (physics, mathematics, computer science, economics, chemistry, biology, etc.). Research program. The Chaire “Stress Testing” is a specific research program between Ecole Polytechnique and BNP Paribas, and is hosted at Polytechnique by the Center of Applied Mathematics https://portail.polytechnique.edu/cmap/en This research project is part of an in-depth reflection on the increasingly sophisticated issues surrounding stress tests (under the impulse of the upcoming European Banking regulation). Simulation of extreme adverse scenarios is an important topic to better understand which critical configurations can lead to financial and systemic crises. These scenarios may depend on complex phenomena, for which we partially lack information, making the modeling incomplete and uncertain. Last, the data are multivariate and reflect the dependency between driving variables. From the above observations, different lines of research are considered: 1) the generation of stress test and meta-modeling scenarios using machine learning 2) the quantification of uncertainties in risk metrics 3) modeling and estimation of multidimensional dependencies Keywords: Bayesian Networks, copulas, dependent data, Deep Learning, Gaussian processes, machine learning, Markov Chain Monte Carlo, meta-modeling, multivariate statistics, rare event simulation, risk metrics, splitting methods, stochastic algorithms, stochastic and Bayesian optimization, uncertainty propagation Candidate profile: • A PhD in Probability and Statistics, or equivalent • A proven track record in quality research, as evidenced by research publications in the top scientific journals and conferences • Solid working knowledge of some of the topics listed above (see keywords), both in research and teaching • Solid working knowledge in the development of numerical methods or data analysis (with Python, R) • An understanding of financial risks is desirable • Good communication and management skills, allowing to be involved in the scientific life of the Chaire Position: 3 years, extension is possible. The teaching load will be about 70 hours/year. Net salary: about 2800€/month depending on the experience How to Apply: Your application should include a Cover Letter, Resume, publications, description of teaching experience. With your application, we ask that you briefly outline your experience against the selection criteria in the position description.
En savoir plus :https://drive.google.com/open?id=1iVZwCZrIshtBVo_gca6NeE5JnfKcp8ei
LecturerChaireStressTest.pdf
Contact :emmanuel.gobet@polytechnique.edu

Page précédente  1  2  3  4  <5> 

 
 
©2019 SFdS
Société Française de Statistique
Institut Henri Poincaré
11 rue Pierre et Marie Curie
75231 Paris cedex 5
Tél. : +33 (0)1 44 27 66 60
Notre site a été supporté par :