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Group Details

Geometric Science of Information

The objective of this group is to bring together pure/applied mathematicians, physicist and engineers, with common interest for Geometric tools and their applications. It notably aim to organize conferences and to promote collaborative european and international research projects, and diffuse research results on the related domains. It aims to organise conferences, seminar, to promote collaborative local, european and international research project, and to diffuse research results in the the different related interested domains.

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    OFFICIAL WEBPAGE

    JEAN-MARIE SOURIAU

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    In May 1969 the groundbreaking book of Jean-Marie Souriau appeared, Structure des Systèmes Dynamiques. We will celebrate, in 2019, the jubilee of its publication, with a conference in honour of the work of this great scientist.
    Welcome to the conference !

    LOCATION
    MAP

    Paris-Diderot Université
    4 Rue Elsa Morante, 75013 Paris

    REGISTRATION

    Just send us an email with your name and your affiliation (if any)…

    SPEAKERS

    • Frédéric Barbaresco (Thales Group, France)
    • Daniel Bennequin (Université Paris Diderot, France)
    • Jean-Pierre Bourguignon (European Research Council, Europe)
    • Pierre Cartier (IHES Paris, France)
    • Maurice Courbage (Université Paris Diderot, France)
    • Dan Christensen (University of Western Ontario, Canada)
    • Thibault Damour (IHES Paris, France)
    • Paul Donato (Aix-Marseille Université, France) Souriau, a synthesis of his work
    • Paolo Giordano (Wolfgang Pauli Institute, Wien, Austria)
    • Serap Gürer (Galatasaray Üniversitesi, Turkey) Differential Forms on Stratified Spaces
    • Patrick Iglesias-Zemmour (Aix-Marseille Université, France) Symplectic Diffeology. Dissipative Thermodynamics in General Relativity
    • Yael Karshon (University of Toronto, Canada)
    • Yvette Kosmann-Schwarzbach (Paris, France)
    • Marc Lachieze-Rey (APC — Université Paris Diderot, France)
    • Martin Pinsonnault (University of Western Ontario, Canada)
    • Elisa Prato (Università degli Studi di Firenze, Italy)
    • Urs Schreiber (Czech Academy of the Sciences, Czech Republic)
    • Jedrzej Sniatycki (University of Calgary, Canada)
    • Roland Triay (Aix-Marseille Université, France)
    • San Vũ Ngọc (Université de Rennes, France)
    • Jordan Watts (Central Michigan University, USA)
    • Alan Weinstein (University of California, Berkeley, USA)
    • Enxin Wu (汕头大学Shantou University, China)

    POSTERS

    If you want to present a poster, just send us an email with your name, affiliation, the title of your poster and possibly a link on a pdf.

    SYLLABUS

    In May 1969 the groundbreaking book of Jean-Marie Souriau appeared, Structure des systèmes dynamiques. We will celebrate, in 2019, the jubilee of its publication, with a conference in honour of the work of this great scientist.

    The influence of Souriau’s work is felt in the areas he has innovated or developed in his own way. It is important to take stock of it, in particular in order to make the current and future generations aware of his original and deep thought.

    The main reasons for organising this conference are the singularity, and at the same time the scope, of the work of Souriau. He was able to create, in his time, a homogeneous group of “Souristes” who for the most part have reached maturity and are able today to convey the originality of this work. It is also time to take stock of the important work to which it has given rise among foreign researchers, many of whom we will invite to speak. The work of Jean-Marie Souriau lives on in different areas of the scientific world and, at different levels of depth, in the development of mathematics and physics, and therefore according to the different temporalities of the history of these disciplines.

    All scholars, old and new, recognize this. Souriau’s work is particularly important work for the relationships he has established and developed between physics and geometry. He is one of the most important founders of symplectic geometry, and the theoretical exploitation of his work in this field is far from exhausted.

    André Lichnerowicz has said that his work could belong to four international scientific unions: mathematics, mechanics, physics and astronomy. But what interests us is not only Souriau the scientist, but also the philosopher. What is striking is the unity of his thought through the variety of his fields of interest. It is likely true that this thought grows deeper as its areas of application expand. The object of our inquiry will be to analyse his thought insofar as it is related to the philosophy of science and even to pure philosophy.

    This conference aims to review the entire work of Jean-Marie Souriau in the five areas in which he worked.

    1. Symplectic mechanics. Symplectic structure of the space of the movements of a dynamic system, action of invariance groups, moment map, symplectic cohomology, barycentric decomposition theorem. Elementary systems (particles): homogeneous symplectic variety, classification by coadjoint orbits.

    2. Geometric Quantization. Prequantization condition, pre-quantum bundle, polarizations, quantification of coadjoint orbits.

    3. Thermodynamics. Geometric statistical equilibria in symplectic manifolds. Vector temperature and thermodynamic dissipative model in general relativity.

    4. General Relativity and Cosmology. General Covariance Principle, Robertson-Walker universe model with cosmological constant.

    5. Diffeology. Renewal of the formal framework of differential geometry by a stable space category by all natural set operations (i.e. complete, complete, Cartesian closed). This includes highly singular spaces that may not even be separated, infinite dimensional spaces, and so on.

    6. Philosophy of Science, Epistemology, History of Science. History of each of the domains evoked (symplectic mechanics, quantification, cosmology and relativity, thermodynamics). In each of these areas Souriau introduced new ideas. These new views have not ceased to be relevant and fruitful. The task of a philosophy of science will be to highlight this novelty.

    As far as philosophy is concerned, a new question has been raised about the importance of this work, in its variety and unity, and in its impact on the philosophy of science and philosophy in general, which we propose to deal with in this conference. Souriau’s originality manifested itself in his will and in his attempts to create new languages. We will analyze, in the philosophy section, this important aspect of his work, most evident in his work in geometry and relativity.

    The Organizers: J.-J. Szczeciniarz & P. Iglesias-Zemmour

    SPONSORS

    Capture du 2018-10-14 10-21-27.png

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    OFFICIAL WEBSITE

    Presentation

    A seminar on Topological and Geometrical Structures of Information has been organized at CIRM in 2017, to gather engineers, applied and pure mathematicians interested in the geometry of information. This year FGSI’19 conference will be focused on the foundations of geometric structures of information. It is dedicated to the triumvirat Cartan - Koszul - Souriau and their influence on the field.

    The conference will take place in Montpellier from Monday 4th February 2019 at 9am until Wednesday 6th February at 1pm.

    Poster
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    Speakers

    • Anton ALEKSEEV (Geneva Univ.)
    • Dmitri ALEKSEEVSKY (Moscow IITP)
    • John BAEZ (Riverside UC)
    • Michel BRION (Grenoble Univ.)
    • Misha GROMOV* (Paris IHES)
    • Patrick IGLESIAS-ZEMMOUR (Marseille Univ.)
    • Yann OLLIVIER (Paris Facebook)
    • Vasily PESTUN (Paris IHES)
    • Aissa WADE (Penn State Univ.)
      *to be confirmed

    Panel sessions :

    • SYMPLECTIC GEOMETRY IN PHYSICS, led by Damien CALAQUE
    • TRIBUTE TO J-L KOSZUL AND J-M SOURIAU, led by Frederic BARBARESCO and Michel N'GUIFFO-BOYOM

    Registration
    https://fgsi2019.sciencesconf.org/registration/index

    Sponsors

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    Abstract
    An overview over recently developed methods for proving decay to equilibrium for dissipative dynamical systems is presented. The methodology is based on Lyapunov functionals, often with the physical interpretation of a (generalized) entropy or free energy.
    The course features a short formal introduction to stochastic processes, aimed at an audience with a PDE background. The concepts of martingales and time reversal of homogeneous Markov processes are used to derive local decay results for relative
    entropies. These are applied to various examples of Levy processes, including applications in kinetic transport theory, in mathematical biology, and in chemical reaction networks. Quantitative decay results are derived from entropyentropy decay inequalities or from inequalities between entropy decay and its time derivative, i.e. by the celebrated Bakry-Emery approach.
    A focus is on hypocoercive problems, where decay to equilibrium holds despite the fact that the decay term for the natural entropy functionals is only semi-denite. Various recent approaches to such problems, mainly in kinetic theory, are compared and unied.
    Finally, examples of nonlinear problems are discussed, and the question of structural assumptions allowing for entropy decay is examined.

    Lundi 8 octobre 2018
    Lundi 15 octobre 2018
    Lundi 22 octobre 2018
    Lundi 29 octobre 2018

    Lundi 5 novembre 2018
    Lundi 12 novembre 2018
    Mercredi 21 novembre 2018
    Lundi 26 novembre 2018
    De 14h à 17h
    Institut Henri Poincaré - Salle 314
    *

    *et exceptionnellement salle 201 le 29/10/18
    11 rue Pierre et Marie 75005 Paris
    Information
    www.sciencesmaths-paris.fr

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    Chercheur/Ingénieur Sénior en Machine Learning
    PDF FILE OF THE ANNOUNCEMENT

    Sophia Antipolis, le 28/05/2018 : Depuis 2002, Median Technologies a élargi les limites de l'identification, de
    l'interprétation, de l'analyse et de la communication des données de l'imagerie dans le monde médical.
    Nous sommes au cœur des solutions innovantes de logiciels en imagerie, pour le développement clinique de
    médicaments, l’aide au diagnostic et le suivi des patients atteints de cancers. Nos clients sont les laboratoires
    pharmaceutiques, les sociétés de biotechnologie, ainsi que les autorités et les institutions de santé à travers le monde.
    Median Technologies se situe à l’intersection de la médecine, de l’imagerie médicale et des technologies de l’information
    et de la communication. Notre équipe, qui inclut aujourd’hui environ 130 collaborateurs en Europe, Asie et aux Etats-
    Unis, combine des expertises scientifiques, techniques, médicales et réglementaires pour développer un logiciel
    innovant d’analyse en imagerie médicale, dans le but d’améliorer la vie des patients atteints de maladies, dans le monde
    entier. Nous sommes guidés par nos valeurs fondamentales : l’innovation de pointe comme objectif, de la qualité dans
    tous ce que nous faisons, du soutien envers nos clients dans la réalisation de leurs objectifs et en nous rappelant de
    toujours faire passer le patient en premier.
    Basés sur la côte d’Azur, avec une filiale sur la côte est des Etats-Unis, nous travaillons dans un contexte international
    et multiculturel particulièrement attractif et épanouissant.

    Dans le cadre de notre recherche et développement en Intelligence Artificielle appliquée à l’imagerie médicale, nous
    recherchons : Chercheur/Ingénieur Sénior en Machine Learning, H/F.
    Intégré dans une équipe multidisciplinaire de recherche et développement dans le cadre du projet iBIOPSY®, vous
    serez le Chercheur/Ingénieur Senior dans la recherche et le développement de solutions d’imageries médicales
    innovantes à l'aide de l'apprentissage par machine et autres méthodes d’IA.
    L'imagerie médicale est l'un des champs les plus prospère dans l'apprentissage par machine. Nous recherchons un
    Scientifique Sénior, enthousiaste, dynamique, organisé, avec une forte expérience ML et d'excellentes compétences en
    communication qui se développeront au cœur de l'innovation technologique.

    Présentation des activités et tâches principales associées au poste
    o Poste rattaché au service Machine Learning and Imaging, sous la responsabilité du Chief Scientific
    Officer
    o Responsabilités :

    1. Vous appliquerez vos connaissances en IA / ML pour développer des solutions innovantes et
      construirez des prototypes de faisabilité en utilisant des données provenant de systèmes
      d'imagerie médicale tels que les IRM et les tomodensitomètres (TDM).
    2. Votre travail comprendra la recherche agile et le développement de nouveaux algorithmes et
      systèmes d'apprentissage automatique. Faisant partie de notre centre d'innovation frontale,
      vous serez activement impliqué dans la recherche, le suivi, l'évaluation et à la mise à profit des
      techniques de rupture, ainsi que des nouvelles tendances industrielles, académiques et
      technologiques.
    3. En outre, vous serez associé au transfert de la technologie et partagerez votre vision avec les
      équipes d'innovation. Vous générerez de la propriété intellectuelle pour l'entreprise. Vous serez
      appelé à rédiger des articles évalués par des pairs, et à présenter des résultats lors de
      conférences industrielles / scientifiques.
    4. Nous vous assisterons dans la création de solutions d'imagerie révolutionnaires reposant sur
      l'intelligence artificielle exploitant le cloud et appliquant des techniques modernes d'IA pour
      créer de la valeur à partir des référentiels d'imagerie et de données cliniques générés par nos
      partenaires de recherche médicale et pharmaceutique. Ces systèmes et services activés par
      l'IA iront au-delà de l'analyse d'image pour transformer la pratique médicale et le
      développement de médicaments.

    o Les responsabilités incluent également la gestion et l'engagement avec nos partenaires technologiques
    stratégiques tiers
    o Les responsabilités futures peuvent inclure la direction d'une équipe de scientifiques en apprentissage
    automatique.

    Profil sollicité
    o Formation : Master ou Doctorat en Mathématiques, Informatique, Ingénierie Electrique ou autre
    domaine connexe
    o Expérience :
    • Minimum 3 ans d’expérience pertinente en Apprentissage Machine
    • Expérience en gestion d'équipe souhaitée
    • Une expérience des réseaux générateurs tels que les GAN serait un atout
    • Auteur sur la recherche connexe
    • Grande expérience de travail avec les frameworks d'apprentissage automatique
    • Solide expérience des technologies opensource pour accélérer l'innovation
    o Connaissances :
    • Connaissance technique approfondie de l'IA, du Machine Learning automatique en vision par
    ordinateur ou dans un domaine connexe
    • Une forte connaissance du traitement des données statistiques, des techniques de régression,
    des réseaux de neurones, des arbres de décision, de la classification, de la reconnaissance
    des formes, des probabilités, des systèmes stochastiques, de l'inférence bayésienne, des
    techniques statistiques et de la réduction de la dimension, est fondamentale
    o Compétences/ Qualités
    • Solides compétences en programmation en R, Python, C ++ ou un autre langage de
    programmation
    • Solides compétences interpersonnelles, de communication et de présentation ainsi qu’une
    capacité à travailler dans une équipe internationale

    Eléments du contrat
    o Poste basé à : Sophia-Antipolis, France
    o Type de contrat : CDI
    o Date de début du contrat : au plus tôt
    o Rémunération : à négocier selon profil

    Avantages offerts par la société
    o Cadre épanouissant
    o Tickets restaurant
    o Restaurant d’entreprise
    o Mutuelle d’entreprise

    MEDIAN Technologies SA au capital de 583 794,45 €
    RCS Grasse – SIRET 443 676 309 00042 – APE 5829C
    Siège social : Les 2 Arcs – Bat B - 1800 route des Crêtes
    06560 Valbonne – France
    Téléphone : +33 (0)4 93 333 777 – Fax : +33 (0)4 92 90 65 99
    Web : www.mediantechnologies.com

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    Official WEBSITE

    Information about the research
    The Division of Applied Mathematics and Statistics at the Department of Mathematical Sciences at Chalmers University of Technology and the University of Gothenburg, together with the Agrifood and Bioscience unit of RISE Research Institutes of Sweden, invites applications for one two-year postdoctoral position starting November 1, 2018, or as agreed. The successful candidate will be offered a one-year employment at Chalmers, followed by a one-year employment at RISE Agrifood and Bioscience.

    The aim of the project is to develop new tools and methods for statistical modeling of random, heterogeneous, porous material structures. This involves both to work with two- and three-dimensional imaging data of real material structures and with simulation of virtual material structures inspired by real materials to understand the connection between structure and mass transport properties (diffusion and flow). The project constitutes part of a collaboration with several major Swedish industries, as well as with experimentalists in academia, and the methods and software that are developed within the project will be applied to real, industry-relevant materials used in for example hygiene products, packaging materials, pharmaceuticals, etc.

    As part of the VINNExcellence Centre SuMo Biomaterials (SuMo), the project ‘Material structures seen through microscopy and statistics’ funded by the Swedish Foundation for Strategic Research, and the project ‘Mass transport properties of soft porous granular materials’ funded by the Swedish Research Council, many tools for image analysis, statistical characterization, and generation of virtual material structures have been developed. Further, within the SuMo Centre, state-of-the-art software for lattice Boltzmann-based diffusion and flow simulations is available.

    The aim is to build upon the accumulated knowledge from these projects and:

    (1) Develop new image analysis and segmentation algorithms for image data. Highly accurate automatic or semi-automatic image analysis methods are crucial for segmentation of imaging data of material structures. This is particularly important for 3D data where data size makes complete manual segmentation very time-consuming.

    (2) Develop new spatial and spatio-temporal models for fiber materials, foams, granular media, etc, using knowledge acquired through studying real materials.

    (3) Perform simulation studies of mass transport properties using available simulation tools developed in related projects together with new methods of generating material structures. Exploring material structures in the computer is important to avoid costly and time-consuming experimental studies.

    The goal is a deep understanding of the relationships between microstructure and properties that will benefit both further research and applications.

    This position is one of three postdoctoral positions within the new project CoSiMa, which is part of the SuMo Biomaterials centre (www.chalmers.se/sumo).

    References
    S Barman, D Bolin. A three‐dimensional statistical model for imaged microstructures of porous polymer films. Journal of Microscopy, 269, 247-258 (2018).

    H Häbel, T Rajala, C Boissier, M Marucci, K Schladitz, C Redenbach, A Särkkä. A three-dimensional anisotropic point process characterization for pharmaceutical coatings. Spatial Statistics, 22, 306-320 (2017).

    M Röding, K Gaska, R Kádár, N Lorén. Computational screening of diffusive transport in nanoplatelet-filled composites: Use of graphene to enhance polymer barrier properties. ACS Applied Nano Materials, 1, 160−167 (2018).

    M Röding, E Schuster, K Logg, M Lundman, P Bergström, C Hanson, T Gebäck, N Lorén. Computational high-throughput screening of fluid permeability in heterogeneous fiber materials. Soft Matter, 12, 6293-6299 (2016).

    About the division and the department
    At the Division of Applied Mathematics and Statistics we conduct research at a high international level in areas such as biomathematics, bioinformatics, computational mathematics, optimisation, mathematical statistics, kinetic theory. More information about our research groups is available on the website http://www.chalmers.se/en/departments/math/research/research-groups/

    We have an international environment with frequent exchanges with other universities around the world. The department provides a friendly, creative, and supportive atmosphere with a steady flow of international guests. At the division there are many committed teachers with extensive and broad experience of all aspects of higher education. Together with the Divisions of Algebra and Geometry and Analysis and Probability we form the academic part of the department of Mathematical Sciences, which is a joint department of Chalmers and the University of Gothenburg, and one of the largest in mathematics in the Nordic countries with a faculty core of about 80. More information about us is available on the website http://www.chalmers.se/en/departments/math/.

    At the Agrifood and Bioscience unit at RISE Research Institutes of Sweden we conduct research and development in food, agriculture, and bioscience related topics including quantitative microscopy, image analysis, computational materials science, hetereogeneous and viscoelastic materials, microbiology and food processing. The unit comprises about 100 people, and is part of the division of Bioscience and Materials at RISE Research Institutes of Sweden. More information about us is available on the website
    http://www.sp.se/en/units/risebiovet/fb/Sidor/default.aspx

    Major responsibilities
    You are expected to pursue a vigorous research program and collaborate with our researchers.

    During the employment at the Department of Mathematical Sciences, we offer you the possibility that up to 20 % of your work may be spent on teaching. RISE Agrifood and Bioscience does not offer teaching.

    Position summary
    Full-time temporary employment. The position is limited to a maximum of two years (1+1).

    Qualifications
    You should have a Ph.D. in Applied Mathematics, Mathematical Statistics, Computational Science, possibly also Physics, or equivalent, completed before the starting date of employment and not earlier than three years before the application deadline. Fluency in English is expected. Experience in image analysis and processing, machine learning, spatial statistics, and good programming skills is meriting.

    Chalmers continuously strives to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.

    Our offer to you
    Chalmers offers a cultivating and inspiring working environment in the dynamic city of Gothenburg.
    Read more about working at Chalmers and our benefits for employees.

    Application procedure
    The application should be marked with Ref 20180454 and written in English. The application should be sent electronically and be attached as pdf-files, as below:

    CV: (Please name the document as: CV, Surname, Ref. number) including:
    • CV, include complete list of publications
    • Previous teaching and pedagogical experiences
    • Two references that we can contact.

    Personal letter: (Please name the document as: Personal letter, Family name, Ref. number) including:
    • 1-3 pages where you introduce yourself and present your qualifications.
    • Previous research fields and main research results.
    • Future goals and research focus. Are there any specific projects and research issues you are primarily interested in?

    Other documents:
    • Attested copies of completed education, grades and other certificates.

    Please use the button at the foot of the page to reach the application form. The files may be compressed (zipped).

    Application deadline: 28 September, 2018

    For questions, please contact:
    Deputy head of Division, Stig Larsson, stig[at]chalmers.se
    Aila Särkkä, aila[at]chalmers.se
    Magnus Röding, magnus.roding[at]ri.se

    *** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***

    Chalmers University of Technology conducts research and education in engineering sciences, architecture, technology-related mathematical sciences, natural and nautical sciences, working in close collaboration with industry and society. The strategy for scientific excellence focuses on our eight Areas of Advance; Building Futures, Energy, Information & Communication Technology, Life Science, Materials Science, Nanoscience & Nanotechnology, Production and Transport. The aim is to make an active contribution to a sustainable future using the basic sciences as a foundation and innovation and entrepreneurship as the central driving forces. Chalmers has around 11,000 students and 3,000 employees. New knowledge and improved technology have characterised Chalmers since its foundation in 1829, completely in accordance with the will of William Chalmers and his motto: Avancez!

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    OFFICIAL WEBPAGE

    October 3rd to October 5th 2018
    Workshop at the Institute Camille Jordan

    Faculté des Sciences et Techniques
    Bâtiment A, salle A 14

    Aim of the workshop

    The aim of the workshop is to bring together researchers at the junction of discrete random structures, in particular random graphs, random walks, and its applications to complex networks.

    Poster of the workshop

    Organizing committee

    • Dieter Mitsche
    • Pascal Grail
    • Pascale Villet

    Speakers

    Julien Barré (Univ. d'Orléans): Rigidity percolation and random graphs
    Oriane Blondel (CNRS, Univ. Lyon 1)
    Jérémie Bouttier (ENS Lyon): Some aspects of random maps coupled with matter systems
    Pierre Calka (Univ. Rouen)
    Philippe Chassaing (Univ. de Lorraine): The impatient collector
    David Coupier (Univ. Valenciennes)
    Josep Diaz (UPC Barcelona): Evolutionary Graph Theory
    Roland Diel (Univ. Nice Côte d'Azur)
    Joachim Giesen (Univ. Jena)
    Emmanuel Jacob (ENS Lyon)
    Lefteris Kirousis (National and Kapodistrian Univ. Athens): The Lovasz Local Lemma: An introduction and some recent results
    Antoine Lejay (INRIA Nancy Grand-Est)
    Grégory Miermont (ENS Lyon)
    Grigory Panasenko (Univ. Saint-Etienne)
    Guillem Perarnau (Univ. Birmingham): Efficient sampling of random colorings
    Vlady Ravelomanana (Univ. Paris 7)
    Christophe Sabot (Univ. Lyon 1)
    Bruno Schapira (Univ. Aix-Marseille)
    Fabio Toninelli (CNRS, Univ. Lyon 1)

    Schedule

    Details will be announced soon.
    Talks start wednesday October 3 after lunch and end Friday October 5 before lunch.

    Registration

    No fee. However, for logistical reasons, registration is mandatory.
    In order to register, please contact us by email: dieter.mitsche(AT)univ-st-etienne.fr, by September 26.

    Practical Information

    The talks will take place in the Faculty of Sciences, room A 14, 23 rue du Docteur Paul Michelon, Saint-Étienne.

    Venue: Address: Institut Camille Jordan, Faculté des Sciences et Techniques, 23 rue du Docteur Paul Michelon, 42023 Saint-Étienne Cedex 2

    How to arrive from Aeroport Lyon Saint-Exupery: The shuttle Ouibus makes the connection form Lyon Saint-Exupery airport to Saint-Etienne main train station.
    Alternative: By Rhône-express (https://www.rhonexpress.fr/) + train (TER Lyon Part Dieu-Saint-Etienne: (https://www.ter.sncf.com/auvergne-rhone-alpes)

    How to arrive from Lyon-Part Dieu or Lyon-Perrache: By train, https://www.ter.sncf.com/auvergne-rhone-alpes (TER journeys to/from Saint-Etienne and Lyon take under 50 minutes).

    How to go from the main station Saint-Etienne Chateaucreux to the Institute Camille Jordan: The city bus company: STAS: http://www.reseau-stas.fr/fr/itineraires/4/JourneyPlanner
    The Bus line M4 takes you from the main train station (Saint-Etienne Châteaucreux) to the faculty of Sciences.

    Accomodation:
    Continental Hôtel ★★
    10 Rue François Gillet - 42000 Saint-Étienne
    Phone: 04.77.32.58.43
    Website: https://www.hotelcontinental42.fr/fr/

    Hôtel du Cheval Noir ★★★
    11 Rue François Gillet - 42000 Saint-Étienne
    Phone: 04.77.33.41.72
    Website: http://www.hotel-chevalnoir.fr/fr

    Access

    Access and Campus Maps

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    The School of Advanced Studies (SAS), University of Tyumen, Russia, is recruiting post-
    docs and professors in biology, ideally specialized in neurobiology but other profiles will be
    considered too. The workload will consist of teaching general undergraduate biology courses
    (about 50% of time), and doing research on the neuroscience of consciousness and free will within
    an interdisciplinary team (e.g. performing Libet-like experiments using EEG, fMRI etc., available
    in Tyumen). If the candidates are not experts in this type of research, they will be given the means
    to become experts; they also have the possibility to devote a (small) part of their research to other
    personal research in biology. After one successful year, the post-docs will be invited to apply for
    a permanent faculty position at the SAS.
    The School of Advanced Studies of the University of Tyumen is a new institution, created
    in 2017 and incentivized by the Russian Federal Government to become a centre of excellence in
    interdisciplinary research and teaching (the students of SAS choose majors in biology, IT,
    humanities and social sciences). The scientists we will recruit will receive western-standard
    salaries and will have a unique opportunity to develop their own research in neurobiology,
    neurophysiology, neuropsychology or related fields, while being offered the possibility to interact
    with other disciplines, notably from humanities and social sciences. For info on the general context
    of the project: https://sas.utmn.ru/en/free-will-en/. For questions, please contact Dr. Louis
    Vervoort at l.vervoort@utmn.ru.
    For interested parties, please submit your application via e-mail to l.vervoort [at] utmn.ru.
    Include a cover letter (explaining the relevance of your application for these positions), a full CV,
    and two letters of recommendation. Applications will be considered from September 1 st 2018
    throughout 2018 until the positions are filled; first applications will be given first attention.

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  • Geo-Sci-Info

    Academic Fellowship positions

    The University of Nottingham is a research intensive university ranked in the top 10 in the UK and in the top 30 of Europe. It has a strong tradition in Cognition, Perception, Mathematical Biology, and structural and functional Imaging. To support further development across these areas, and stimulate new research opportunities, the University has recently made a major investment in Computational Neuroscience.

    As part of this investment we are inviting applications for three independent fellowships (3 years). The positions are ideal for researchers with a strong vision that are planning to develop their own research group in a supportive, interdisciplinary environment with outstanding research facilities.

    We are interested in candidates working across a broad spectrum of research topics areas in Computational Neuroscience, including functional neuroimaging, neural networks, and models of cognition. Research methodologies could include numerical simulation, machine learning, theoretical neuroscience, and innovative data analysis. The Fellows will be based in the School of Psychology and/or Mathematical Sciences.

    For the online application form see
    https://www.nottingham.ac.uk/jobs/currentvacancies/ref/SCI219418

    Informal inquiries:
    Prof Mark van Rossum, mark.vanrossum [at] nottingham.ac.uk, or
    Prof Mark Humphries, lpzmdh [at] exmail.nottingham.ac.uk.

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  • Geo-Sci-Info

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    OFFICIAL WEBPAGE

    DOWNLOAD PROGRAM

    Conférence-débat de l'Académie des sciences, de 14h30 à 16h45, dans la Grande salle des séances de l’Institut de France - Inscription obligatoire avant le 9 octobre 2018

    Organisateur
    Alain Berthoz, professeur honoraire au Collège de France, membre de l'Académie des sciences et de l’Académie des technologies.

    Intervenants

    • Neil Burgess, professeur et directeur de l’Institute of Cognitive Neuroscience, University College London, membre de la Royal Society et de l’Academy of Medical Sciences
    • Laure Rondi-Reig, directrice de recherche au CNRS à l’Institut de Biologie Paris–Seine, Université Pierre-et-Marie-Curie
    • Alain Berthoz, professeur honoraire au Collège de France, membre de l'Académie des sciences et de l’Académie des technologies
    • Daniel Bennequin, professeur émérite au département de mathématiques de l’université Paris Diderot.

    Résumé
    Le thème général de cette séance sera d’exposer des découvertes et théories récentes concernant le traitement cérébral de l’espace et plus particulièrement la flexibilité des stratégies cognitives et la diversité des réseaux de traitement des divers espaces d’action.
    Neil Burgess décrira les divers types de neurones de la formation hippocampique qui codent la place, la direction, les bords, leur organisation en grilles et les relations avec les objets. Il décrira un modèle mathématique de transformation entre les divers référentiels spatiaux (égocentré, allocentré etc.) et son utilisation pour prédire des symptômes de déficits de la mémoire spatiale dans des pathologies post-traumatiques.
    Laure Rondi-Reig décrira les réseaux neuronaux impliqués dans des activités de navigation spatiale, l’apprentissage et les troubles de la mémoire, dans le cas du vieillissement par exemple. Des données expérimentales sur les mécanismes neurophysiologiques et la diversité des réseaux corticaux et sous corticaux de la cognition spatiale et des modèles inspirés des neurosciences computationnelles seront présentés.
    Alain Berthoz proposera que le cerveau traite avec des réseaux différents et des géométries différentes pour les divers espaces (corps, préhension, locomoteur, environnemental). Il décrira des données récentes sur les bases neurales des changements de perspective, le développement chez l’enfant des fonctions visuo-spatiales et l’intervention de la manipulation des référentiels spatiaux dans l’empathie et son implication en pathologie psychiatrique.
    Daniel Bennequin proposera que pour guider l’adaptation des actions et des perceptions, les cerveaux des animaux et de l’homme mettent en place une variété de géométries, Euclidiennes et non Euclidiennes, et de dynamiques. L’exposé présentera un travail sur une nouvelle sorte de géométrie : un topos d’espaces au-dessus d’une catégorie (site) représentant la préparation et l’exécution d’une classe de mouvements; par exemple la préhension, la locomotion, la navigation, l’imagination.

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  • Geo-Sci-Info

    Capture du 2018-07-16 10-08-30.png

    OFFICIAL WEBSITE

    This ICML workshop seeks to broaden the role of geometric models and thinking in machine-learning research.

    The interplay between machine learning and geometry is an active field of research drawing the attention of researchers from many fields as it offers not only beautiful mathematical and statistical theory but also substantial impact on important real-world problems in machine learning. Examples of this interplay include, but are not limited to:

    • geometric insights into deep learning (helping us to better understand and improve these models);
    • statistical models that respect and exploit the constraints of geometric data ("statistics on manifolds");
    • (Riemannian) manifold learning;
    • viewing probability distributions as points on a nonlinear manifold ("information geometry");
    • optimization over nonlinear manifolds;
    • Wasserstein spaces and their applications;
    • understanding the effect of encoding group invariances (e.g. rotation invariance) on the intrinsic geometry of the data space, which becomes a quotient space.

    This ICML workshop is co-located with ICML, IJCAI and AAMAS in Stockholm.

    The Bosch center for AI generously sponsors a prize for the best abstract, which will be presented at the workshop.

    Confirmed Speakers

    Venue

    The workshop takes place at the ICML conference venue, room A4.

    Organizers

    The conference is jointly organized by:

    For matters regarding the conference, you can contact the organizers at gimli.meeting[at]gmail.com.

    We are grateful for funding from the Bosch Center for Artificial Intelligence, the Villum Fonden Young Investigator program and the European Research Council (ERC) through a starting grant.

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