Consulter les offres d’emploi

Analyse de données caractéristiques de dimensions de poids lourds en vue de la détection de fraude
Publiée le 25/03/2024 10:34.
Référence : Stage M2 en Statistique et Data Science -.
Stage, Champs-sur-Marne.
Entreprise/Organisme :Université Gustave Eiffel
Niveau d'études :Master
Sujet :La plupart des codes de la route et autres réglementations sur les poids maximum des véhicules routiers de type poids lourds fixent des limites liées au nombre d'essieux. Avec l'introduction envisagée de la verbalisation automatique à l'aide de systèmes de pesage en marche (WIM), il faut que le système sache précisément le nombre d'essieux du véhicule mis en cause en cas de surcharge. Or si des essieux sont relevés, le système WIM voit et compte n-p essieux si p essieux sont relevés. Il va donc appliquer la limite de charge pour n-p essieux. En outre la législation est floue sur la valeur maximale du poids autorisé. Celle liée au nombre total d'essieux, indiqué sur la carte grise du véhicule, ignore totalement le fait qu'un ou plusieurs essieux soient relevés, ou le nombre d'essieux au sol au moment du contrôle. Cet aspect juridique et réglementaire sera à traiter par les autorités compétentes. Quoi qu’il en soit il apparait donc crucial de détecter correctement le nombre d’essieux relevés afin de pouvoir identifier la bonne catégorie et les éventuelles fraudes à sanctionner. Le cœur du travail à réaliser consistera en une analyse statistique de bases de mesures WIM actuelles issues de différentes autoroutes européennes. Ces données existent d’ores et déjà en particulier grâce au projet européen SETO (Smart Enforcement of Transport Operations) qui fait partie du programme Horizon. L'objectif de SETO est de créer un cadre pour l'application existante et future du transport intelligent dans des contextes multimodaux et transfrontaliers. Les études menées dans [1] et [2] proposent de comparer la distribution des essieux (ou séquences des distances inter-essieux d’un véhicule) à des clusters liés à la silhouette des PL en service. Une méthode k-means est proposée. Cependant, son emploi reste assez discutable si l’on veut proposer une méthodologie susceptible de détecter avec précision les véhicules fraudeurs. Un état de l’art, s’appuyant par exemple sur [3], sur les méthodes les plus adaptées à ce problème sera la première priorité de ce travail (CAH, modèles logistiques, méthodes neuronales, combinaisons de modèles, …). Dans un second temps, on mettra en œuvre les plus pertinentes et un travail de comparaison quant à leurs performances sera également mené. Références [1] Quoy O, Interdistances et silhouettes de poids lours sur autoroute, Revue Générale des Routes (RGRA), 1er trimestre 2021 [2] Stocchetti A, Statistiques de comptage de poids lourds et détermination de silhouettes, Rapport de la Société de Calcul Mathématique, octobre 2020 [3] Tuffery S, Data Mining et Statistiques Décisionnelles. La science des données, Technip, 2017 Disciplines abordées : probabilités, statistiques, analyse de données, Data scientist
Date de début :avril/mai 2024
Durée du contrat :5 à 6 mois
Rémunération :600 euros
Description :Voir la fiche détaillée du sujet
En savoir plus :https://pics-l.univ-gustave-eiffel.fr/
Stage_M2_UGE.pdf
Contact :dimitri.daucher@univ-eiffel.fr
Ingénieur.e en biostatistique
Publiée le 25/03/2024 10:34.
CDD, Lille.
Entreprise/Organisme :Plateforme Bilille - UAR 2014 - US 41 Plateformes Lilloises en Biologie et Santé
Niveau d'études :Master
Date de début :Prise de fonction dès que possible à partir de Mai 2024
Durée du contrat :CDD de 12 mois renouvelable
Rémunération :Suivant l’expérience et les grilles de l'Université de Lille.
Secteur d'activité :Plateforme de Bioinformatique et Biostatistique
Description :La plateforme de bioinformatique et biostatistique Bilille est l’une des 8 plateformes scientifiques et technologiques de l’unité PLBS (Plateformes Lilloises en Biologie et Santé) au service d’unités de recherche académiques en sciences de la vie et de la santé. Afin de renforcer son pôle biostatistique, Bilille recrute un.e ingénieur.e d’étude (IE) ou de recherche (IR) en biostatistique afin de réaliser des projets d'analyse de données biologiques au profit de diverses unités de recherche de la métropole lilloise. Formation minimum : master ou diplôme d’ingénieur en (bio)statistique
En savoir plus :https://bilille.univ-lille.fr/news/detailed-news/join-bilille-team
202403_IE_IR_biostat_offre_poste.pdf
Contact :bilille@univ-lille.fr
Poste de MCF "Statistique, Statistique Computationnelle, Apprentissage" à INSA Lyon/ICJ/Dept IF
Publiée le 25/03/2024 10:34.
Référence : MCF INSA LYON.
CDI, INSA de Lyon / Institut Camille Jordan.
Entreprise/Organisme :INSA de Lyon
Niveau d'études :Doctorat
Date de début :Septembre 2024
Description :voir fiche jointe
En savoir plus :https://math.univ-lyon1.fr/icj/
2024_Fiche_Profil-MCF-Maths-IF-ICJ.pdf
Contact :direction-icj@math.univ-lyon1.fr
STATISTICIEN(NE) - Ingénieur d'études
Publiée le 25/03/2024 10:34.
Référence : STATISTICIEN(NE) Laboratoire Reshape/Impulse.
CDD, Rockefeller, Lyon 08.
Entreprise/Organisme :Inserm U1290 Reshape, équipe Impulse
Niveau d'études :Master
Date de début :Dès que possible
Durée du contrat :12 mois renouvelables
Rémunération :Grilles Inserm : A partir de 2 445,87€ brut mensuel en fonction de l'expérience
Secteur d'activité :Recherche en Santé publique
Description :Dans le cadre du développement de l’équipe IMPULSE (Inserm U1290 Reshape), le/la candidat(e) aura pour mission la conception, la mise en oeuvre et la valorisation des résultats d’études épidémiologiques sur des produits de santé à partir de grandes bases de données, en particulier celles du Système National des Données de Santé (SNDS). Il/Elle mènera ses missions sous la supervision de la responsable de l’équipe IMPULSE (Marie VIPREY).
En savoir plus :https://www.impulse-research.fr / https://www.reshapelab.fr/
Offre d'emploi_statisticien IMPULSE_2024.pdf
Contact :reshapelyon@gmail.com
Postdoctoral Position in Machine Learning
Publiée le 25/03/2024 10:34.
Référence : MIRACLE-MLLT-24.
Postdoc, Timone Faculty of Medical and Paramedical Sciences in Marseille, France.
Entreprise/Organisme :SESSTIM - Aix-Marseille University
Niveau d'études :Doctorat
Date de début :As soon as possible, depending on administrative recruitment deadlines
Durée du contrat :12 months, with the possibility of extension
Rémunération :Postdoctoral level; Aix-Marseille University salary scale
Secteur d'activité :Machine learning; Computer science; Engineering; Mathematics; Medical science
Description :The candidate will work in the multidisciplinary "Quantitative Methods and Medical Information Processing (QuanTIM)" team, comprising researchers in epidemiology and public health, statisticians, biostatisticians, computer scientists and data scientists. More specifically, he/she will be assigned to a project involving the application and development of Artificial Intelligence techniques to data from cancer registries. The aim of the work will be to develop or adapt a machine learning methodology in order to estimate excess mortality in the case of insufficiently stratified general population life tables. Activities: As part of the MIRACLE project (Méthodologie et Intelligence aRtificielle pour lA recherche épidémiologique en CancéroLogiE sur bases de données), funded by the French Ligue contre le Cancer, the candidate will contribute, for the benefit of patients and to decision-making in public health, to the enhancement of cancer databases, particularly the population-based ones. In this context, a key indicator measured in the general population is net survival, which represents the survival that would be observed in a hypothetical world where the studied disease is the only cause of death. By considering mortality due to other causes, which is derived from general population life tables stratified by certain variables, it enables comparisons to be made between populations and trends. However, using insufficiently stratified general population life tables leads to biased estimates of excess mortality. Different approaches have been considered and different models have been proposed to estimate excess cancer mortality for variables not directly observed in general population life tables. However, the existing models are based on certain assumptions that may be considered too strong given the needs and epidemiological questions. The candidate will familiarize himself/herself with various existing approaches and models, and then investigate the contribution of machine learning-based approaches based. He/she will develop or adapt a methodology based on machine learning (k-means, random forests or others) to estimate excess mortality in the case of insufficiently stratified general population life tables. The methodology developed should be adaptable to the situation where the number of variables not directly observed in the general population life tables is not limited. The candidate will assess the performances of these different methods through simulation studies. He/she will place particular emphasis on the interpretation of the methods, focusing on the epidemiological interpretability of the results obtained. He/she will implement the whole in an R package, preferably, or in another language depending on what is most suitable for practical application. In collaboration with other project investigators, he/she will write the article(s) on this work for publication in international peer-reviewed journals whether methodological or applied.
En savoir plus :https://sesstim.univ-amu.fr/fr/offre-d-emploi
PostDoc_MIRACLE-MLRT.pdf
Contact :nathalie.graffeo@univ-amu.fr
Stage de Master 2 : Exploitation de données longitudinales pour le monitoring de bioprocédé
Publiée le 25/03/2024 10:34.
Référence : refOnirisDomulo.
Stage, Nantes.
Entreprise/Organisme :Oniris VetAgroBioNantes
Niveau d'études :Master
Date de début :mars 2024
Durée du contrat :5 à 6 mois
Rémunération :600
Secteur d'activité :Etablissement d'enseignement et recherche
Description :L’objectif du stage sera de mettre en place un pipeline analytique spécifique pour la valorisation des données omiques longitudinales issues de bioprocédés. Différents défis statistiques seront à résoudre (Kodikara et al. 2022). Des jeux de données omiques (metataxonomique, métagénomique, métabolomique) issues d’échantillons prélevés dans des bioréacteurs de laboratoire sont disponibles. Elles proviennent d’expériences réalisées dans l’unité PROSE pour évaluer les conséquences de différents stress salins sur les performances de la digestion anaérobie
En savoir plus :NA
DOMULO_Stage_M2_StatSC_PROSE_2024.pdf
Contact :veronique.cariou@oniris-nantes.fr
3-year PhD position in Statistics - Machine Learning\ for Biological processes in Lyon, France
Publiée le 25/03/2024 10:34.
Référence : 3-year PhD position in Statistics - Machine Learning for Biological processes in Lyon, France.
Thèse, Lyon.
Entreprise/Organisme :Institut Camille Jordan and International Agency for Research on Cancer, Lyon
Niveau d'études :Master
Date de début :2024 ou 2025
Durée du contrat :36 months
Rémunération :2100 euros gross salary
Secteur d'activité :Recherche académique
Description :Applications are invited for a 3-year PhD position in statistics and machine learning at the International Agency for Research on Cancer (IARC, World Health Organization, Lyon, France) and Ecole Centrale de Lyon (ECL, Lyon, France). The PhD candidate will join the MOBiL project (Multi-omics data integration to investigate biological mechanisms underlying the link between lifestyle behaviors and gastro-intestinal cancers), which is one of the~11 "Projets Structurants" funded within the Shape-Med Lyon initiative.
En savoir plus :https://math.univ-lyon1.fr/icj/
MOBiL.pdf
Contact :yohann.de-castro@ec-lyon.fr
Poste de Professeur Maths & Stats Appliqué, Université de Melbourne
Publiée le 25/03/2024 10:33.
CDI, Melbourne, Australia.
Entreprise/Organisme :University of Melbourne
Niveau d'études :Doctorat
Durée du contrat :Permanent
Description :The Faculty of Science, University of Melbourne is opening multiple appointments at the Associate Prof and Prof levels across a range of areas including Maths & Stats, with a focus on multi-disciplinary research. The position will be based at the School of Mathematics and Statistics (> 80 continuing staff, > 140 PhD students, https://ms.unimelb.edu.au/) with opportunities to interact with our Melbourne Integrative genomics initiative (https://sites.research.unimelb.edu.au/integrative-genomics). We are looking for candidates with a focus on methodological developments and applications to various domains. Applications close: 14 Apr 2024 11:55 PM AUS Eastern Standard Time
En savoir plus :https://jobs.unimelb.edu.au/en/job/916297/associate-professorprofessor-faculty-of-science
Contact :kimanh.lecao@unimelb.edu.au
Statistical learning for the detection and classification of circulating tumor cells
Publiée le 25/03/2024 10:33.
Postdoc, Statistical learning for the detection and classification of circulating tumor cells.
Entreprise/Organisme :Inria Lille
Niveau d'études :Doctorat
Date de début :Mai 2024
Durée du contrat :18 mois
Rémunération :2653 (before taxes)
Description :This postdoc project aims at developing a statistical learning method for the detection and classification of circulating tumor cells in the bloodstream based on their biophysical characteristics
En savoir plus :https://recrutement.inria.fr/public/classic/fr/offres/2021-04274
2021-04274-offre3-fr.pdf
Contact :sophie.dabo@inria.fr
Stochastic rainfall generators and impact studies on flood risk in Montpellier
Publiée le 25/03/2024 10:33.
Référence : Idil Eau_PIUM_A.
Thèse, Université de Montpellier - Inria.
Entreprise/Organisme :Université de Montpellier - Inria
Niveau d'études :Master
Sujet :The first objective of the thesis will be to develop a spatio-temporal stochastic rainfall generator, to be implemented for the study of the Montpellier region, in southern France associated with a specific climate. This tool will simulate extreme and moderate rainfall, as well as dry periods. The originality of the proposed approach will consist in combining two crucial aspects in a single model: (i) stochastic modeling of rainfall events similar to those actually observed; (ii) high spatial resolution on a fine pixel grid and high temporal resolution. The simulated data can then be used to feed a numerical model of urban runoff. The second objective of the thesis will then be to conduct correlative studies between the inputs and outputs of the numerical model, developing new methodological tools for sensitivity analysis and risk measurement in the context of spatial extremes. From a methodological point of view, this thesis will draw heavily on extreme value theory, spatio-temporal statistics, risk statistics and graphical models. It will exploit and extend the tools of probabilistic machine learning and risk analysis
Date de début :01/10/2024
Durée du contrat :Three years
Description :When to apply? Before April 15, 2024 . This PhD is part of the Eau-PI-UM project funded by the IDIL program. The general objective of the project is to propose mathematical and physical models to better understand urban flooding and contribute to a decision support system. This PhD offer, which covers the statistical part of the project, is coupled with another PhD, which addresses the physical issues. The successful candidate will therefore be required to collaborate with researchers from other disciplines. Skills required : Statistics/Probability; R and/or Python Keywords : extreme values, spatio-temporal statistics, sensitivity analysis, climate hazards
En savoir plus :https://idil.edu.umontpellier.fr/inscrivez-vous-dans-un-doctorat-interdisciplinaire/
phd_IDIL_2024_stat.pdf
Contact :gwladys.toulemonde@umontpellier.fr
Neural network study of urban flood risk and the impact of extreme spatio-temporal rainfall events
Publiée le 25/03/2024 10:33.
Référence : Idil Eau_PIUM_B.
Thèse, Université de Montpellier - Inria.
Entreprise/Organisme :Université de Montpellier - Inria
Niveau d'études :Master
Sujet :Deep learning models such as LSTM (long short-term memory) have proved their effectiveness in a hydrological context, for example in rainfall-runoff modelling, but very few studies have tackled flood prediction in terms of water extent and depth. One of the main reasons for this is the need for a large learning database, in a field where validation data is almost non-existent. The aim of the thesis will be to develop an artificial intelligence model based mainly on the results of multi-scale hydraulic models. As the latter are based on a discretisation of space into cells (finite volumes), we plan to use AI models using a graph representation of the domain (Graph Neural Network), in which the nodes would contain the results in terms of water level and speed in the cells and the edges would represent the possible transfers of water and energy between cells. Particular attention will be paid to respecting the laws of physics that govern flows in shallow water, i.e. the laws of conservation of mass and momentum, thus placing us in the field of hybrid AI. The application to the city of Montpellier will enable impact studies to be carried out for different scenarios.
Date de début :01/10/2024
Durée du contrat :Three years
Description :This thesis is part of the Eau-PI-UM project funded by the IDIL program. The general objective of the project is to propose mathematical and physical models that will provide a better understanding of flooding in urban environments. This thesis, which covers the hydraulic part of the project, is coupled with another thesis, which addresses the statistical issues of rainfall fields for the simulation of extreme events. During impact studies carried out by design offices, highly simplifying assumptions are made about rainfall fields: uniform in space and at best 'double triangles' in time. In study areas such as Montpellier, the use of spatio-temporal fields seems necessary for a correct representation of the so-called “episodes Cévenols”. The successful candidate will therefore be required to collaborate with researchers from other disciplines.
En savoir plus :https://idil.edu.umontpellier.fr/inscrivez-vous-dans-un-doctorat-interdisciplinaire/
phd_IDIL_2024_hydro.pdf
Contact :carole.delenne@umontpellier.fr
Junior statistical methodologist
Publiée le 04/03/2024 12:57.
Référence : Junior_stat.
CDI, France.
Entreprise/Organisme :Saryga
Niveau d'études :Doctorat
Secteur d'activité :Biostatistics
Description :Junior statistical methodologist Permanent contract, full time, 100% remote in France -- Saryga -- Saryga is a company dedicated to support innovation in statistics and decision-making in healthcare. Its main activity is to assist pharmaceutical companies, biotechnology companies and hospitals on developing and using highly advanced statistical methodologies to optimise drug development plans and clinical trials. With an active collaboration with academia, it also contributes to the research and the publication of novel approaches. We are a small but dynamic company, looking for talented statisticians to develop our activities. At Saryga, you will have the opportunity to develop your career and take greater responsibilities within a flexible working environment. Want to learn more about us? Visit saryga.com or contact gaelle.saint-hilary@saryga.com. -- Tasks and responsibilities -- As junior statistical methodologist, you will: • Provide statistical input and technical support on methods related to clinical trial designs, complex models, quantitative decision-making and/or biomarker research • Perform research work to develop new methodologies, write and / or participate to writing scientific publications • Collaborate with academia (supervision of students, cooperation with universities on research projects…) • Provide trainings to statisticians and non-statisticians You will have the opportunity to work on various therapeutic areas, often in complex settings with great value to the patients (rare diseases, innovative mechanisms of action…). The position is a permanent employment contract, full time, 100% remote in France (with some travels to attend meetings or conferences). -- Qualifications -- Requirements • Doctoral degree (PhD) in Statistics or Applied Mathematics, with 0-3 years of experience and no previous permanent employment contract (“jeune docteur”) • Published research work • Knowledge of clinical trials designs • Knowledge of statistical models for clinical trials • Excellent programming skills (in R and/or Python) • Oral and written communication skills, ability to present complex concepts clearly • Fluency in written and spoken English Nice-to-have • Knowledge in one or several of the following areas: Bayesian statistics, biomarkers, historical data, decision-making, causal inference, meta-analyses, PK/PD, drug benefit-risk assessment, data-visualisation tools • Knowledge of regulatory processes for drug developments -- How to apply? -- Send your CV and cover letter to gaelle.saint-hilary@saryga.com. We look forward to receiving your application!
En savoir plus :https://saryga.com/careers/
2024_Saryga_Job_Statistical_methodologist_junior.pdf
Contact :gaelle.saint-hilary@saryga.com
Statistical methodologist (2-5y experience)
Publiée le 04/03/2024 12:57.
Référence : Exp_stat.
CDI, France.
Entreprise/Organisme :Saryga
Niveau d'études :Doctorat
Secteur d'activité :Biostatistics
Description :Statistical methodologist (2-5y experience) Permanent contract, full time, 100% remote in France -- Saryga -- Saryga is a company dedicated to support innovation in statistics and decision-making in healthcare. Its main activity is to assist pharmaceutical companies, biotechnology companies and hospitals on developing and using highly advanced statistical methodologies to optimise drug development plans and clinical trials. With an active collaboration with academia, it also contributes to the research and the publication of novel approaches. We are a small but dynamic company, looking for talented statisticians to develop our activities. At Saryga, you will have the opportunity to develop your career and take greater responsibilities within a flexible working environment. Want to learn more about us? Visit saryga.com or contact gaelle.saint-hilary@saryga.com. -- Tasks and responsibilities -- As statistical methodologist, you will: • Provide statistical input and technical support on methods related to clinical trial designs, complex models, quantitative decision-making and/or biomarker research • Perform research work to develop new methodologies, write and / or participate to writing scientific publications • Collaborate with academia (supervision of students, cooperation with universities on research projects…) • Provide trainings to statisticians and non-statisticians You will have the opportunity to work on various therapeutic areas, often in complex settings with great value to the patients (rare diseases, innovative mechanisms of action…). The position is a permanent employment contract, full time, 100% remote in France (with some travels to attend meetings or conferences). -- Qualifications -- Requirements • Doctoral degree (PhD) in Statistics or Applied Mathematics, with 2-5 years of experience on clinical trials • Published research work • Proactive mindset with the ability to make innovative proposals and suggestions • Mandatory: Good knowledge and proven experience in clinical trials designs (early and / or late phase) • Good knowledge of statistical models for clinical trials • Knowledge of Bayesian statistics • Excellent programming skills (in R and/or Python) • Oral and written communication skills, ability to present complex concepts clearly • Fluency in written and spoken English Nice-to-have • Knowledge in one or several of the following areas: Biomarkers, historical data, decision-making, causal inference, meta-analyses, PK/PD, drug benefit-risk assessment, data-visualisation tools • Knowledge of regulatory processes for drug developments -- How to apply? -- Send your CV and cover letter to gaelle.saint-hilary@saryga.com. We look forward to receiving your application!
En savoir plus :https://saryga.com/careers/
2024_Saryga_Job_Statistical_methodologist_experienced.pdf
Contact :gaelle.saint-hilary@saryga.com
SENIOR BIOSTATISTICIAN
Publiée le 04/03/2024 12:57.
Référence : GHL2024SB2.
CDI, Paris.
Entreprise/Organisme :GHLconsult cabinet de recrutement
Niveau d'études :Doctorat
Date de début :dès que possible
Rémunération :80K€
Secteur d'activité :biotechnologies
Description :Laboratoire conduisant des études cliniques en France et à l'international (1 phase I, 3 phases II & 8 phases III - Amérique du Nord, Amérique du Sud, Europe, Asie) recherche un Biostatisticien Senior Missions • Author the Statistical Sections of Protocol. • Propose and Review the Study design. • Calculate the sample size. • Review the Case Report Form (CRF). • Review the Edit Check Document (specifically for critical modules like RECIST 1.1 etc.). • Write the randomization specifications and coordinate and finalize all the randomization activities with the IWRS vendor. • Author Statistical Analysis Plan (interim and final as appropriate). • Perform the Statistical Analysis (Efficacy and Safety (key safety like Adverse Events)) using SAS. • Ensure quality of all the outputs developed. • Perform the role of validator as appropriate. • Provide Statistical Consultancy on an ongoing basis for projects. • Perform Futility and Efficacy analysis as appropriate for interim analysis and interact with third party independent Statistician. • Defend the Statistical Analysis at the IDMC meetings as appropriate. • Write the specifications for the efficacy analysis. Review the Specifications for the Safety Analysis. • Organize Data Review Meetings (equivalent to Blinded Data Review (BDR) or Dry Run) and lead all the statistical discussions. • Work Collaboratively with the data management, Clinical Operations, Medical Writing and the Pharmacovigilance team as appropriate. • Provide inputs to the regulatory affairs for all the discussions with the health authorities (e.g. ANSM, EMA, FDA). • Review the Clinical Study Report and provide statistical inputs as appropriate. • Perform exploratory analysis as appropriate. Profil • Female or male • Ph.D. in Statistics with minimum 3 years of relevant pharmaceutical (or CRO) industry work experience or Masters in Statistics or equivalent with minimum 5 relevant pharmaceutical (or CRO) industry work experience. • Good Knowledge of SAS. • Preliminary working knowledge on R. • Good Understanding of CDISC Concepts. • Good understanding of ICH guidelines. • Decent written and verbal English communications skills. • Good Team Player. • Innovative mindset. • Good interpersonal skills. • Good time management. Terms and conditions • Permanent contract (CDI) to be filled as soon as possible • Paris based post office • Salary to be defined according to profile and experience • The company sponsors the EU work visa if needed
En savoir plus :www.ghlconsult.com
Senior Biostatistician permanent contract Paris 2024.pdf
Contact :gilleslaurent@ghlconsult.com
Stage de M2 Data Science
Publiée le 04/03/2024 12:57.
Référence : Stage M2 Data Science - Time series.
Stage, Evry, IBGBI institute.
Entreprise/Organisme :LaMME Université d'Evry
Niveau d'études :Master
Sujet :Change-Point Detection For Time Series A Novel Approach For Efficient Computation With Robust Loss (détails dans le pdf)
Date de début :autour de début mai
Durée du contrat :4 à 6 mois
Rémunération :environ 650 euros (le standard de l'Université)
Secteur d'activité :Mathématiques - Data Science
Description :Voir le pdf Stage pour un étudiant de MASTER 2 en Data Science, IA, Maths appliquées
En savoir plus :http://www.math-evry.cnrs.fr/doku.php
InternshipM2_DataScience_Evry.pdf
Contact :vincent.runge@univ.evry.fr

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