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  • Geo-Sci-Info

    Capture du 2020-05-27 09-37-13.png

    In the context of our research and development in artificial intelligence applied to medical imaging, we are looking for: Data Science and Machine Learning Research Scientist M/F

    Integrated into a multidisciplinary research and development team within the iBiopsy® project, you are a scientist in the research and development of innovative medical imaging solutions using machine learning and other AI methods.

    Medical imaging is one of the fastest growing fields in machine learning. We are looking for an enthusiastic, dynamic, and organized Senior Scientist/Engineer with strong ML experience, excellent communication skills who will thrive at the heart of technological innovation.

    Presentation of activities and main tasks linked to the job

    • Position under the supervision of Head of Data Science and the Chief of Science and Innovation Officer

    Responsibilities:

    1. You will work on content based-image retrieval in medical imaging. You will build efficient search engine services in clinical applications.
    1. You will apply your AI/ML knowledge to develop innovative and robust biomarkers using data coming from medical imaging systems such as MRI and CT scanners and other data sources.
    1. Your work will involve agile research and development of novel machine learning algorithms and systems. Being part of our front-end innovation organization, you will actively scout, keep track of, evaluate, and leverage disruptive technologies, and emerging industrial, academic and technological trends.
    1. You will work with software development team as well as clinical science team.
    1. In addition, you will transfer technology, and share insights and best practices across innovation teams. You will generate intellectual property for the company. You will be expected to author peer reviewed papers, present results at industry/scientific conferences.
    1. We look at you to building breakthrough AI-enabled imaging solutions leveraging cloud computing and apply supervised and unsupervised Machine Learning techniques to create value from the imaging and clinical data repositories generated by our medical research and pharmaceutical industry partners. These AI enabled systems and services go beyond image analysis to transform medical practice and drug development.

    Searched profile :

    • Education: PhD in in Mathematics, Computer Science or related fields
    • Main skills and Experience required:
    • Minimum 5 years of relevant work experience in (deep) machine learning
    • Experience with Medical Imaging, CT/MRI, image signatures, large scale visual information retrieval, features selection
    • Relevant experience with Python, R, DL frameworks (i.e. Pytorch, Keras, Tensorflow) and standard packages as Scikit-learn, Numpy, Scipy, Pandas
    • Semi-Supervised Learning, Self-supervised Learning, Reinforcement Learning, Adversarial methods.
    • Multimodal feature extraction
    • Author on related research publication / conferences
    • Strong experience with opensource technologies to accelerate innovation

    Knowledge:

    • In depth technical knowledge of AI, deep learning and computer vision
    • Strong fundamental knowledge of statistical data processing, regression techniques, neural networks, decision trees, clustering, pattern recognition, probability theory, stochastic systems, Bayesian inference, statistical techniques and dimensionality reduction

    Additional qualities:

    • Strong interpersonal, communication and presentation skills as well as ability to work in global team
    • Fluent in written and oral English

    Legal

    • Job location: Sophia Antipolis, France
    • Contract: Permanent, Open-Ended
    • Start: As Soon As Possible
    • Offered salary: will depend on candidate’s skills and experience.

    Please apply on our website : https://mediantechnologies.com/job-search/#!careers

    posted in Jobs offers - Call for projects read more
  • Geo-Sci-Info

    Capture du 2020-05-27 09-29-30.png
    In the context of our research and development in artificial intelligence applied to medical imaging, we are looking for: Data Structuring and Clustering Research Scientist M/F

    Integrated into a multidisciplinary research and development team within the iBiopsy® project, you are a scientist in the research and development of innovative medical imaging solutions using machine learning and other AI methods.

    Medical imaging is one of the fastest growing fields in machine learning. We are looking for an enthusiastic, dynamic, and organized Senior Scientist/Engineer with strong ML experience, excellent communication skills who will thrive at the heart of technological innovation.

    Presentation of activities and main tasks linked to the job

    • Position under the supervision of the Head of Data Science and the Chief of Science and Innovation Officer.

    • Responsibilities:

    1. You will work on scalable data clustering techniques and develop your know how for knowledge discovery and exploration towards robust biomarkers. You will conduct clustering validity studies

    2. You will work on large scale data mining and feature exraction in medical imaging. You will build and contribute to develop innovative and robust biomarkers for personalized medicine

    3. Your work will involve agile research and development of novel machine learning algorithms and systems. Being part of our front-end innovation organization, you will actively scout, keep track of, evaluate, and leverage disruptive technologies, and emerging industrial, academic and technological trends.

    1. You will work with software development team as well as clinical science team.
    1. In addition, you will transfer technology, and share insights and best practices across innovation teams. You will generate intellectual property for the company. You will be expected to author peer reviewed papers, present results at industry/scientific conferences.
    1. We look at you to building breakthrough AI-enabled imaging solutions leveraging cloud computing and apply supervised and unsupervised Machine Learning techniques to create value from the imaging and clinical data repositories generated by our medical research and pharmaceutical industry partners. These AI enabled systems and services go beyond image analysis to transform medical practice and drug development.

    Searched profile

    • Education: PhD in in Mathematics, Computer Science or related fields
    • Main skills and Experience required:
    • Minimum 3 years of relevant work experience in machine learning
    • Experience with Medical Imaging, CT/MRI, image signatures, large scale visual information retrieval, features selection
    • Relevant experience with Python, R, DL frameworks (i.e. Pytorch, Keras, Tensorflow) and standard packages as Scikit-learn, Numpy, Scipy, Pandas
    • Data structure inference models, clustering and semi-supervised learning, knowledge discovery and data mapping, saliency map
    • Multimodal feature extraction
    • Author on related research publication / conferences
    • Strong experience with opensource technologies to accelerate innovation

    Knowledge:

    *In depth technical knowledge of AI, deep learning and computer vision

    • Strong fundamental knowledge of statistical data processing, regression techniques, neural networks, decision trees, clustering, pattern recognition, probability theory, stochastic systems, Bayesian inference, statistical techniques and dimensionality reduction

    Additional qualities:

    • Strong interpersonal, communication and presentation skills as well as ability to work in global team
    • Fluent in written and oral English

    Legal

    • Job location: Sophia Antipolis, France
    • Contract: Permanent, Open-Ended
    • Start: September 2020
    • Offered salary: will depend on candidate’s skills and experience.

    Please apply on our website : https://mediantechnologies.com/job-search/#!careers

    posted in Jobs offers - Call for projects read more
  • Geo-Sci-Info

    Capture du 2020-05-12 18-26-07.png
    OFFICIAL WEBSITE
    MEMBER RESOURCES
    This website is dedicated to featuring national resources developed by ISO members to support the fight against COVID-19.

    posted in COVID19 open Database ressources and challenges read more
  • Geo-Sci-Info

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    Alibaba Cloud - Free CT Image Analytics for COVID-19
    Official WEBPAGE
    This technology can assist realizing quantitative analysis, speeding up CT image analytics, avoiding errors caused by fatigue and adjusting treatment plans in time.
    Free for public research institution
    Email Your Submission: Free Computational and AI Platforms to Help Research, Analyze and Combat COVID-19 ("Program") is intended to support public research institutions worldwide for the research analysis and prevention of COVID-19. This technology is subject to availability upon confirmation. You can submit the summary and description of your research project to wanqing.hwq [at] alibaba-inc.com. All submissions will be reviewed for technical feasibility, and eligible applicants will be contacted for more details and the next steps of the process. Once the submission is successful, the applicant will get a certain amount of coupon according to the project, which is valid for 3months. The coupon can be used for all Alibaba cloud products, including HPC, ECS, and GPU, excluding marketplace products and 3rd party products.
    Disclaimer: The technology is not intended to, by itself and without the exercise of professional judgment and clinical evaluation, diagnose any medical condition or disease or conclusively indicate the absence of any disease, including COVID-19 and the technology is not a substitute for diagnosis and treatment by a certified medical professional. The technology has not been thoroughly tested, and are not guaranteed in any way to be accurate, useful, sufficient, satisfactory, available, or otherwise fit for any purpose. To the maximum extent permissible under applicable law, the Solution is provided "AS IS," "WITH ALL FAULTS," and without any warranties or service guarantees.
    Note: The accuracy is calculated using the model trained on about 5000 samples, and is tested based on a sample size of 660 tests with a 1:1:1 ratio of cases of COVID-19 pneumonia, common pneumonia, and other conditions.

    Whole Genome Sequencing Analysis for COVID-19
    Official WEBPAGE
    When facing a severe epidemic such as COVID-19, rapid and accurate virus screening and detection is particularly important for maintaining control. The AI algorithm avoids the high missed detection rate of nearly 40% of PCR, and can accurately detect virus mutations and shorten the duration of genetic analysis of suspected cases from hours to just 30 minutes, greatly reducing the time of virus screening and detection.
    To read disclaimer, click to see Disclaimer in FAQ.

    • Rapid and accurate testing to improve the handling of local outbreaks
    • Core algorithm optimization and comprehensive monitoring of COVID-19 development and changes
    • Quick deployment and easy to use with modular and simplified operation and configuration

    Elastic High Performance Computing Technology
    Official WEBPAGE
    The development of new drugs and vaccines for COVID-19 requires large amounts of data analysis, as well as large-scale literature screening and scientific computing. HPC and AI technology helps scientific research institutions to perform viral gene sequencing, conduct new drug research and development, and shorten the research and development cycle. The Global Health Drug Discovery Institute (GHDDI) has established a scientific data sharing platform and an AI drug screening platform for COVID-19 with the support of this center's open AI computing power. Some research institutions and universities have increased the speed of biological information transmission by 5 times, and reduced the virtual screening time for antiviral drugs from one month to one week.

    posted in COVID19 open Database ressources and challenges read more
  • Geo-Sci-Info

    CovidBanner-1.png
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    LINK TO WEBSITE

    Covid-19 Interactive Dashboard – MULTIVAC

    OPEN SCIENCE
    Open Source and Open Data

    This app was developed by using open data and open-source libraries. Some of the useful APIs, data sources, cisualizations, analysis and open-source libraries:
    Libraries

    • Streamlit
    • Spark NLP
    • JohnSnowLabs Healthcare
    • Apache Spark
    • Tensorflow
    • Tensorflow Hub
    • Plotly
    • Matplotlib

    APIs

    • COVID-19 Grafana API (repo): JSON API to visualize stats in Grafana
    • COVID-19 GraphQL API (repo)
    • CovidAPI.info (repo): Lightweight, Superfast REST API built to be consumed by dashboards.
    • COVID-19 Ruby Gem

    Data Sources

    Visualizations

    • Covid19 Visualizer (repo): Covid19 Graphical Visualizer
    • EU stats report on COVID-19 (repo): COVID-19 tracker for EU countries
    • CoronaStatistics.live (repo): COVID-19 Global Report
    • COVID-19 World (repo): COVID-19 Global Report
    • COVID-19 Comparator (repo): Coronavirus cases comparator by countries, from chosen date and number of days (PWA)
    • Mobile Friendly COVID-19 Report (repo): Coronavirus daily report in a mobile friendly website (PWA)
    • COVID-19 Daily Report (repo): Coronavirus daily report, updated hourly
    • COVID-19 GLOBAL Report (repo)
    • covid-charts (repo): chart widget with Coronavirus stats for specified country
    • COVID-19 Global Chart (repo): Chart GeoMap with last status by country.
    • COVID-19 Stats (repo): A simple mobile friendly dashboard visualizing the latest stats of the COVID-19 outbreak.
    • Corona.log (repo): A simple COVID-19 data checker per region
    • COVID-19 How Bad Is It (repo): Live graphs with latest news involving Covid-19,
    • COVID-19 Sri Lanka Tracker (repo): Live Updates of COVID-19 Patients in Sri Lanka
    • COVID-19 Countries Trends & Comparison (repo): Country comparison of COVID-19 cases, with per-capita and growth views.
    • felipec covid-19 (repo): Trajectory of confirmed COVID-19 cases per country after 100 in logarithmic scale and growth factor.
    • COVID-19 Global Report (repo): Vue.js app for monitoring the spread of the new coronavirus
    • COVID-19 Regional Relative TimeSeries (repo): Normalized regional comparative timeseries.
    • COVID-19 Country Travel Bans (repo): An interactive map showing countries with travel restrictions and infection counts.
    • COVID-19 Stats and Trends (repo)
    • COVID Reports (repo): Coronavirus trends comparison by country
    • #daysbehinditaly (repo): Number of days various countries are behind Italy in total COVID-19 cases assuming similar case growth rate
    • Covid-19 Project to track the spread of coronavirus (repo): Coronavirus information by country
    • Covid-19 Progress Reports by Country (repo): Coronavirus (Fight against) Progress by country
    • COVID-19-LK (repo): A Sri Lankan COVID-19 Tracker with a map and dark theme <3
    • COVID-19 Mauritius Statistics (repo): A simple page with stats about the current COVID-19 situation in the small island of Mauritius.
    • Flattening the Curve by Country | COVID-19 🦠 (repo): A simple dashboard to showcase flattening of the curve by each country affected with COVID-19 - plotted over time.
    • World map and country comparison timeline: Select multiple countries on the map for a clean comparison of how the number of cases develop.
    • COVID-19 Panel for Digital Signage (repo): Digital Signage-ready and configurable Panel with COVID-19 data.
    • COVID-19 Trends (repo): Simple charts showing COVID-19 trends
    • Covid-19 Race (repo) A basic html5/css/js webapp to compare the cases from a select few countries.
    • COVID-19 India dashboard (repo) - A simple dashboard made with Flask specifically for India with stats of various states and predictions of what's going to happen in the next five days.
    • Open COVID19 Map (repo) Open map visualization with alternative data sources, containment scores, testing rate projection, replay mode
    • I am Covid -19 🦠 (repo) - Visualization of the covid-19 dataset using Nuxtjs(vuejs), Graphql and valuable information about getting through the Covid-19 pandemic.
    • Simple COVID-19 Tracker (repo): Mobile-friendly and minimal page that displays the current total count of coronavirus cases and deaths in a selected region.
    • COVID-19 Report (repo): Coronavirus information by country in a mobile-friendly SPA.
    • Visualizing COVID-19 with D3 (repo): A responsive D3-based data visualization that leverages a Sankey diagram to display the breakdown of the worldwide COVID-19 cases.
    • Coronavirus-meter (repo): Coronavirus meter provides statistics from cases all around the world. View cases from each country up to two months before. Coronavirus cases, deaths, recovered in statistical numbers from all around the world.
    • Telegram COVID-19 Monitoring Telegram alert everyday with the statistics of COVID-19 in each country.
    • Coronavirus Infections (repo): Track Coronavirus infections, deaths, recovers and active cases per country in chart and table.
    • Corona in Charts (repo): Corona graphs for each country with total cases, active cases, recovered and fatalities.
    • COVID-19 Monitoring And Charting(repo): World COVID-19 Tracking, historical data and overview using NodeJS Server
    • COVID-19 Reaction Tracker (repo): Track user reactions across the globe
    • COVID-19 Data Visualization Using R Shiny(repo): Data Summary, Data Visualization, World Map and differnt Analytics plots.
      *Made in r shiny
    • covid19-psvita-data: An app for viewing COVID-19 Data and graphs on a Playstation Vita
    • COVID-19 Timeline: A Flutter app for tracking COVID-19 data
    • COVID-19 in Numbers (repo): Covid-19 stats and charts by country. Made with Blazor.
      Corona-Virus-Numbers: Android and iOS app for visualising COVID-19 graphs developed using Flutter

    Analysis

    • COVID-19 Trends and Growth Rate: A Python implementation of growth rate and other trend analysis
    • Are we dead yet (repo): Live graphs of confirmed, infected and infection rate. Outbreak normalised for comparison.
    • epidemic-simulator (repo): Mathematical model using Macroscopic Rate Equations for simulating the future of the epidemic
    • Coronavirus Cases, Deaths, and Recoveries by Country (repo) - a blog post with charts that update daily
    • COVID-19 Best fit evolution Visualizing the evolution of a best-fit logistic curve over time, showing the difficulty of predicting the number of future cases and deaths
    • PowerBI-driven COVID-2019 Tracking: Power BI Desktop dashboard based on JSON data about COVID-2019 spread

    posted in COVID19 open Database ressources and challenges read more
  • Geo-Sci-Info

    Capture du 2020-04-13 22-06-29.png

    OFFICIAL WEBPAGE

    The Milken Institute is currently tracking the development of treatments and vaccines for COVID-19 (coronavirus).

    This document contains an aggregation of publicly-available information from validated sources. It is not an endorsement of one approach or treatment over another, but simply a list of all treatments and vaccines currently in development.

    Given the immediacy of the current public health emergency, we believe it is important to make the data accessible to the public in its current form.

    This overview will be updated as new findings come to light. We ask that you check this page on a regular basis.
    Capture du 2020-04-13 22-09-34.png

    image.png

    posted in COVID19 open Database ressources and challenges read more
  • Geo-Sci-Info

    Capture du 2020-05-12 18-20-36.png
    OFFICIAL WEBSITE COVID-19 imaging datasets at EIBIR
    eibir-logo_275x70.png
    Capture du 2020-05-12 18-17-41.png

    A paper in Arxiv "COVID-CT-Dataset: A CT Scan Dataset about COVID-19"
    Jinyu Zhao (UC San Diego), Yichen Zhang (UC San Diego), Xuehai He (UC San Diego), and Pengtao Xie (UC San Diego, Petuum Inc)

    LINK TO THE PAPER
    CT scans are promising in providing accurate, fast, and cheap screening and testing of COVID-19. In this paper, we build a publicly available COVID-CT dataset, containing 275 CT scans that are positive for COVID-19, to foster the research and development of deep learning methods which predict whether a person is affected with COVID-19 by analyzing his/her CTs. We train a deep convolutional neural network on this dataset and achieve an F1 of 0.85 which is a promising performance but yet to be further improved.

    The data and code are available at:
    https://github.com/UCSD-AI4H/COVID-CT
    eibir-logo_275x70.png
    Data Description
    The COVID-CT-Dataset has 349 CT images containing clinical findings of COVID-19. They are in ./Images-processed/CT_COVID.zip

    Non-COVID CT scans are in ./Images-processed/CT_NonCOVID.zip

    We provide a data split in ./Data-split

    The meta information (e.g., patient ID, DOI, image caption) is in COVID-CT-MetaInfo.xlsx

    The images are collected from COVID19-related papers from medRxiv, bioRxiv, NEJM, JAMA, Lancet, etc. CTs containing COVID-19 abnormalities are selected by reading the figure captions in the papers. All copyrights of the data belong to the authors and publishers of these papers.

    posted in COVID19 open Database ressources and challenges read more
  • Geo-Sci-Info

    Ph.D. and Postdoc positions in Applied Mathematics
    The Chair of Applied Analysis - Alexander von Humboldt Professorship at the Department of Mathematics of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), in Erlangen (Germany) led by Professor Dr. Enrique Zuazua, is looking for outstanding candidates to fill several

    OFFICIAL WEBPAGE

    Ph.D. and Postdoc positions in Applied Mathematics

    Das Aufgabengebiet umfasst u. a.
    In the broad area of Applied Mathematics, the Chair develops and applies methods of Analysis, Computational Mathematics and Data Sciences to model, understand and control the dynamics of various phenomena arising in the interphase of Mathematics with Engineering, Physics, Biology and Social Sciences.

    We welcome applications by young and highly motivated scientist to contribute to this exiting joint AvH-FAU effort. Possible research projects include but are not limited to:

    • Analysis of Partial Differential Equations (PDE).
    • The interplay between Data Sciences, numerics of PDE and Control Systems.
    • Control of diffusion models arising in Biology and Social Sciences.
    • Modelling and control of multi-agent systems.
    • Hyperbolic models arising in traffic flow and energy transport.
    • Waves in networks and Markov chains.
    • Fractional PDE.
    • Optimal design in Material Sciences.
    • Micro-macro limit processes.
    • The interplay between discrete and continuous modelling in design and control.
    • The emergence of turnpike phenomena in long-time horizons.
    • Inversion and parameter identification.
    • Recommendation systems.
    • Development of new computation tools and software.

    Wünschenswerte Qualifikation
    We look for excellent candidates with expertise in areas of applied mathematics, PDE analysis, control theory, numerical analysis, data sciences and computational mathematics who enjoy interdisciplinary work.

    Bemerkungen
    The Chair contributes to the development of a new Center of Research at FAU, in the broad area of "Mathematics of Data", conceived as a highly visible interdisciplinary research site, an incubator for future collaborative research grants and a turntable for the key research priorities of FAU. The recruited candidates will have the added opportunity to participate in this challenging endeavour.

    How to apply:

    Applications, including cover/motivation letter, curriculum vitae, list of publications, statement of research and two or three names of experts for reference should be submitted via e-mail as a single pdf file to secretary-aa@math.fau.de before April 30th
    , 2020.

    Any inquiries about the positions should be sent to Professor Dr. Enrique Zuazua (positions-aa@math.fau.de). Applications will be accepted until the positions are filled.

    FAU is a member of "The Family in Higher Education Institutions" best practice club and also aims to increase the number of women in scientific positions. Female candidates are therefore particulary encouraged to apply. In case of equal qualifications, candidates with disabilities will take precedence.

    For more detailed information about the Chair, please visit [Chair of Applied Analysis - Alexander von Humboldt Professorship]https://en.www.math.fau.de/applied-analysis/

    Bewerbung
    secretary-aa [at]math.fau.de

    posted in Jobs offers - Call for projects read more
  • Geo-Sci-Info

    Project Manager Position to launch the Erlangen Center for Mathematics of Data (ECMD)
    FAU is launching an ambitious project to establish the new ERLANGEN CENTER FOR MATHEMATICS OF DATA (ECMD)
    OFFICIAL WEBPAGE
    Project Manager Position to launch the "Erlangen Center for Mathematics of Data (ECMD)"

    Das Aufgabengebiet umfasst u. a.
    The ECMD is anticipated as a highly visible interdisciplinary research center, an incubator for future collaborative research grants and a hub for the key research priorities of FAU. It will be anchored in the Department of Mathematics, coordinating activities with other groups, Departments and Centers at FAU and in its perimeter, in the broad field of Mathematical and Data Sciences.

    With this goal, we aim to integrate a Project Manager so to contribute to define the strategic plan and launch the start-up of the center under the direction of Professor Dr. Enrique Zuazua (Chair Applied Analysis - Alexander von Humboldt Professorship) in collaboration with FAU partners and other collaborating institutions.

    We search for a full-time Project Manager (part-time contracts could also be considered) with excellent organizational skills, and interest in R&D project management.

    The activities to be developed include:

    • Design of institutional structure and procedures
    • Fund raising and support in applications for third party funding
    • Strategic integration into the FAU innovation agenda
    • Coordination with partner institutions
    • Organization of scientific events
    • Dissemination activities and social media
    • Budget management and monitoring
    • HR management
    • General organization
    • Notwendige Qualifikation
    • Master´s degree. PhD would be an asset
    • Training and experience in R%D project management would be desirable
    • Collaborative and competitive intelligence
    • Professional command of German and English

    Wünschenswerte Qualifikation
    Organizational thinking
    Team player mentality and service-orientation
    Self-organized, responsible and highly proactive working style
    Strong cross-cultural communication skills (written and verbal communication in German and English) to weave, foster and maintain working relationships with different international sectors
    Result orientation and objective fulfilment

    Bemerkungen
    Immediate incorporation into the organization.

    The ECMD will offer a lively research environment, financial support for networking and training, and an intensive supervision within a large and interactive team.

    The appointment is initially limited for a period of two years and can be extended for additional three years, or longer, according to the evolution of the Center.

    In its pursuit of academic excellence, FAU is committed to equality of opportunity and to a proactive and inclusive approach, which supports and encourages all under-represented groups, promotes an inclusive culture and values diverstiy. FAU is a family-friendly employer.

    Please submit your electronic application as a single pdf file* including a motivation letter, vita, diplomas and list of potential reference persons, no later than April 30, 2020 to secretary-aa@math.fau.de (cc: enrique.zuazua@fau.de). Please refer to "*Manager-ECMD" in the reference line of the email.

    posted in Jobs offers - Call for projects read more
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