Announcement Postdoc in statistical learning at Gustave Eiffel University - GRETTIA laboratory



  • Classification of spatio-temporal series. Application to the analysis of water quality within of a dynamic network.


  • Keywords: dynamic network, spatio-temporal data, classification of temporal series, unsupervised learning, water quality


  • The evaluation of water quality within distribution networks remains a crucial subject for health and environmental protection issues. With this in mind, managers are brought continuously carry out measurements relating to the quality and flow of water using sensors specific data distributed throughout the network, which generates large amounts of spatiotemporal data.


  • AT these data are added to those from the hydraulic simulation, which can also be used for characterize the dynamics of water within its distribution network.


  • The objective of this postdoc is the advanced analysis of this data distributed in time and space (network) using statistical learning techniques, in order to extract a synthetic view of the dynamics of changes in water quality.


  • The case study will be that of a water network in Ile de France, which is equipped with sensors making it possible to acquire masses of physicochemical data such as temperature, electrical conductivity, chlorine concentration, or flow rate.


  • Particular attention will be paid to unsupervised methods of classification and segmentation time series, in particular those based on latent stochastic processes which provide a flexible framework for summarizing the dynamics of the evolution of temporal data.


  • Variants of these methods could be developed in order to classify the points of the network according to the temporal and spatial dynamics of water quality, and taking into account the complex nature (time lags and distortions, incompleteness) of the associated time series.


  • The missions entrusted to the post-doctoral fellow will relate to the development and practical implementation such methods. The tasks to be carried out will be:


  • (1) familiarization with and elementary exploration of data from water distribution networks,


  • (2) development of classification algorithms automatic of complex time series based on models with dynamic latent variables,


  • (3) the development of IT tools to perform this data processing.


  • Profile: candidates must hold a doctoral thesis in the disciplinary fields of machine learning, statistics or series modeling temporal with an interest in real applications; they may also hold a thesis in the field of hydraulics and with a strong experience in big data analysis.


  • A current use of R, Python or Matlab software / languages ​​is essential for this position.


  • To apply, send a CV and a cover letter to the following addresses:


  • Allou Samé: [email protected]


  • Latifa Oukhellou: [email protected]


  • Pierre Mandel: [email protected]


  • Main place of work: Gustave Eiffel University, GRETTIA Laboratory, Champs-sur-Marne,


  • Secondary workplace: Veolia Eau d´Ile-de-France, DACE - Studies, Research and Development, Nanterre


end-of-studies internship



  • Hello, You will find attached a subject of end-of-studies internship for students in master 2 or 5th year of engineering school


  • entitled "MERLE - Multimodal Effective Representation Learning of Evolution of birds" The internship will take place at LIRIS and LGL in Lyon.


  • Please send a CV, a cover letter and transcripts for the current and previous year to Mathieu Lefort ([email protected]) and Stefan Duffner ([email protected]). Sincerely, Stefan Duffner


Master's internships, PhD and postdoc positions in Bordeaux, France



  • The INTENDED AI Chair (https://intended.labri.fr) aims to develop principled methods for handling inconsistent, incomplete, and uncertain data.


  • It brings together experts on knowledge representation and reasoning, database theory, and medical informatics to explore how to exploit formally represented knowledge (constraints, ontologies) and logical reasoning to holistically tackle a range of data quality issues.


  • We are currently seeking highly motivated candidates for the following positions within the INTENDED project:


  • * Master's internship: "Reasoning with hard and soft constraints to repair and query inconsistent data"


  • * Master's internship: "Ontology-driven phenotyping from electronic health records"


  • * 2 three-year PhD positions (ideally as continuations of the preceding internships)


  • * 1 two-year postdoc position


  • Details on the available positions, required background, and application procedures can be found at: https://intended.labri.fr/hiring.html


  • If you're interested in developing principled yet practical approaches to tackling data quality, please get in touch!


  • Best regards, and a happy new year to all!


  • Meghyn Welcome CNRS Senior Research Scientist


  • LaBRI, University of Bordeaux https://www.labri.fr/perso/meghyn/


Postdoctoral fellowship: Artificial Intelligence for Digital Pathology



  • General information — Keywords : digital pathology, computer vision, deep learning, immunotherapy, Whole Slide


  • — Duration : between 18 and 24 months. To start early 2022.


  • — Institutes: University of Paris, Laboratoire d'Informatique Paris Descartes (LIPADE), SIP (Intelligent Systems of Perception) team & Centre Georges Francois Leclerc (Dijon hospital) & Hôpital Ambroise-Paré (Boulogne hospital)


  • — Location: 45 rue des Saints-Pères, 75006 Paris (LIPADE), France


  • — Supervision : Ass. Prof. Nicolas Loménie and Camille Kurtz ([email protected])


  • — Application : Please send a cover letter, a CV and contact of 2 referees to Nicolas Loménie with Camille Kurtz in cc. The position is opened until filled.


  • More information here: https://w3.mi.parisdescartes. fr/sip-lab/files/postdocs/2021-2022/postdoc2022_LIPADE_AI_COLOPREDICT.pdf


  • -- Camille KURTZ Senior Lecturer - A/Prof


  • University Institute of Technology (IUT of Paris) Laboratoire d'Informatique Paris Descartes (LIPADE, EA 2517)


  • Phone : +33 1 76 53 03 07 Web : www.math-info.univ-paris5.fr/~ckurtz/


offer of internship at the end of studies (Master 2 or 3rd year of engineering cycle)



  • Hello Please find attached an offer of internship at the end of studies (Master 2 or 3rd year of engineering cycle).


  • This internship focuses on a project "Explainable artificial intelligence algorithms for DECISION SUPPORT SYSTEM IN CLINICAL TOXICOLOGY" as part of a collaboration between the Pharmacotoxicology Department, the LBBE laboratory and the LIRIS laboratory of the Université Lyon 1.


  • Location: Pharmacotoxicology and Telework Service Duration: 6 months, from March 2022


  • Applications should send DR Kim An NGUYEN: [email protected]


  • CV


  • cover letter


  • recent academic results


  • Thanks in advance, Kind regards


Post-doc position on brain-computer interfaces



  • Post-doc position on brain-computer interfaces


  • We are seeking a postdoc candidate to work on the CHIST-ERA project "Brainsourcing for Affective Attention Estimation" (BANANA). The project aims at leveraging crowdsourcing brain signals to estimate visual attention and affective responses to visual stimuli. BANANA is an interdisciplinary and coordinated effort with university partners in Luxembourg (coordinator), Finland, Poland, and Spain (us).


  • Location: Institute of New Imaging Technologies (INIT), Universitat Jaume I, Castelló, Spain.


  • Duration: ~3 years starting in early 2022


  • Salary: around 33,000 € gross annual (competitive for the cost of living in our city, check at numbeo.com)


  • Expertise in some of the following topics are desirable:


  • Brain-computer interfaces (BCI): EEG, fNIRs


  • Machine and Deep Learning (self-supervised learning, multi-modal fusion, etc.)


  • Computer Vision (computational salience in images/videos, video processing, visual attention, etc.)


  • (Interactive) Information Visualisation


  • Eye tracking, gaze analysis


  • Human emotion and cognition, particularly (visual) attention


  • Human-Computer Interaction (HCI)


  • For a few more details, please see shorturl.at/mqxK4


  • For either informal enquiries, or expressions of interest (+ CV), please contact V. Javier Traver ([email protected]) before December 31st, 2021.


Multiple Postdoctoral Fellow Opportunities, Khalifa University, UAE



  • We invite applications for multiple Postdoctoral positions in the field of computer vision and machine learning. The candidates are expected to work on projects related to medical image analysis, object detection and classification in video data, and quality control using image and video data.


  • These projects will be conducted in the C2PS and KUCARS


  • Requirements: Experience in deep learning techniques for object detection,


  • object classification, semantic segmentation, instance semantic segmentation.


  • Experience in advanced deep learning models GAN, CyleGAN, GNN, Transformers.


  • Experience in Linux operating system and familiarity with deep learning libraries and dependencies


  • Proficient in English language (written and oral).


  • Relevant scientific track record in major computer vision /machine learning venues.


  • Desired but not compulsory:


  • Experience in Whole Slide Image analysis with application to nucleolus detection, cell classification tissue phenotyping.


  • Experience in predictive models using video data or any sequential visual data.


  • Experience in meta-learning and domain adaptation.


  • The candidates should have a proven ability to do excellent scientific research in computer vision and machine learning, as evidenced by their publications.


  • Highly competitive, tax-free, salary and benefits will be offered to successful candidates.


  • Interested candidates must submit, via email, a cover letter, a detailed curriculum vitae, and 2-3 relevant publications to Prof. Naoufel Werghi : [email protected]


  • Naoufel Werghi Professor Electrical Engineering and Computer Science


  • P O Box 127788, Abu Dhabi, UAE T +971 2 312 4039 [email protected] ku.ac.ae