{"id":24907,"date":"2026-06-22T16:18:55","date_gmt":"2026-06-22T14:18:55","guid":{"rendered":"https:\/\/www.uni.lu\/snt-en\/?post_type=research-projects&p=24907"},"modified":"2026-06-22T16:18:56","modified_gmt":"2026-06-22T14:18:56","slug":"resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat","status":"publish","type":"research-projects","link":"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/","title":{"rendered":"Resource Management in Satellite Communications with Dynamic Topologies: Machine Learning Algorithms for Variable Input-Output Dimensions (ReadyVioSat)"},"content":{"rendered":"\n\n\n
\n

\nAbout<\/h2>\n\n\n<\/div><\/div><\/div><\/div>\n\n\n\n\n
\n \n
\n
\n
\n

\n Project team <\/h2>\n
    \n
  • \n
    \n
    \n
    \n
    \n \n <\/figure>\n <\/div>\n
    \n

    Ti Ti NGUYEN<\/h3>

    <\/p>

    \n \n \n View profile<\/span> <\/span>\n \n \n <\/svg>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/li>\n \n \n
  • \n
    \n
    \n
    \n
    \n \n <\/figure>\n <\/div>\n
    \n

    Ons AOUEDI<\/h3>

    <\/p>

    \n \n \n View profile<\/span> <\/span>\n \n \n <\/svg>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/li>\n
  • \n
    \n
    \n
    \n
    \n \n <\/figure>\n <\/div>\n
    \n

    Vu Nguyen HA<\/h3>

    <\/p>

    \n \n \n View profile<\/span> <\/span>\n \n \n <\/svg>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/li>\n
  • \n
    \n
    \n
    \n
    \n \n <\/figure>\n <\/div>\n
    \n

    Muhammad AWAIS<\/h3>

    <\/p>

    \n \n \n View profile<\/span> <\/span>\n \n \n <\/svg>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/li>\n \n <\/ul>\n <\/div>\n <\/div>\n <\/div>\n<\/section>\n\n\n
    \n \n
    \n
    \n
    \n

    \n Keywords <\/h2>\n
      \n
    • \n Satellite Communication<\/span>\n <\/li>\n
    • \n Resource management<\/span>\n <\/li>\n
    • \n Scalability<\/span>\n <\/li>\n
    • \n Generalizability<\/span>\n <\/li>\n
    • \n Joint Optimization and Machine Learning<\/span>\n <\/li>\n
    • \n Machine Learning for Dynamic Systems<\/span>\n <\/li>\n
    • \n Spectrum management<\/span>\n <\/li>\n
    • \n Algorithms for Beamforming<\/span>\n <\/li>\n
    • \n Routing<\/span>\n <\/li>\n <\/ul>\n <\/div>\n <\/div>\n <\/div>\n<\/section>\n","protected":false},"excerpt":{"rendered":"

      As satellite networks become increasingly dynamic and complex, traditional optimisation approaches struggle to keep pace. This project develops advanced machine learning models designed specifically for these evolving environments, enabling networks to adapt to changing conditions while maintaining performance and reliability. The research focuses on creating solutions that are feasible to deploy, adaptable across scenarios, and generalisable to future satellite network architectures.<\/p>\n","protected":false},"author":399,"featured_media":24905,"parent":0,"menu_order":0,"template":"","meta":{"featured_image_focal_point":{"x":0.1,"y":0.45},"show_featured_caption":false,"ulux_newsletter_groups":"","uluxPostTitle":"","uluxPrePostTitle":"","_trash_the_other_posts":false,"_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"0","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false,"rpp_rp_identifier":"24901","rpp_taxonomies_in_sync":true},"research-project-status":[271],"research-project-type":[263],"field-of-interest":[295],"organisation":[184,195],"authorship":[399],"acf":[],"yoast_head":"\nResource Management in Satellite Communications with Dynamic Topologies: Machine Learning Algorithms for Variable Input-Output Dimensions (ReadyVioSat) - SnT I University of Luxembourg<\/title>\n<meta name=\"description\" content=\"As satellite networks become increasingly dynamic and complex, traditional optimisation approaches struggle to keep pace. This project develops advanced machine learning models designed specifically for these evolving environments, enabling networks to adapt to changing conditions while maintaining performance and reliability. The research focuses on creating solutions that are feasible to deploy, adaptable across scenarios, and generalisable to future satellite network architectures.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Resource Management in Satellite Communications with Dynamic Topologies: Machine Learning Algorithms for Variable Input-Output Dimensions (ReadyVioSat)\" \/>\n<meta property=\"og:description\" content=\"As satellite networks become increasingly dynamic and complex, traditional optimisation approaches struggle to keep pace. This project develops advanced machine learning models designed specifically for these evolving environments, enabling networks to adapt to changing conditions while maintaining performance and reliability. The research focuses on creating solutions that are feasible to deploy, adaptable across scenarios, and generalisable to future satellite network architectures.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/\" \/>\n<meta property=\"og:site_name\" content=\"SnT EN\" \/>\n<meta property=\"article:modified_time\" content=\"2026-06-22T14:18:56+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/06\/22161051\/SnTproject_ReadyVioSat-1.png\" \/>\n\t<meta property=\"og:image:width\" content=\"715\" \/>\n\t<meta property=\"og:image:height\" content=\"661\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Estimated reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/\",\"url\":\"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/\",\"name\":\"Resource Management in Satellite Communications with Dynamic Topologies: Machine Learning Algorithms for Variable Input-Output Dimensions (ReadyVioSat) - SnT I University of Luxembourg\",\"isPartOf\":{\"@id\":\"https:\/\/www.uni.lu\/snt-en\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/06\/22161051\/SnTproject_ReadyVioSat-1.png\",\"datePublished\":\"2026-06-22T14:18:55+00:00\",\"dateModified\":\"2026-06-22T14:18:56+00:00\",\"description\":\"As satellite networks become increasingly dynamic and complex, traditional optimisation approaches struggle to keep pace. This project develops advanced machine learning models designed specifically for these evolving environments, enabling networks to adapt to changing conditions while maintaining performance and reliability. The research focuses on creating solutions that are feasible to deploy, adaptable across scenarios, and generalisable to future satellite network architectures.\",\"breadcrumb\":{\"@id\":\"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/#breadcrumb\"},\"inLanguage\":\"en-GB\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-GB\",\"@id\":\"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/#primaryimage\",\"url\":\"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/06\/22161051\/SnTproject_ReadyVioSat-1.png\",\"contentUrl\":\"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/06\/22161051\/SnTproject_ReadyVioSat-1.png\",\"width\":715,\"height\":661},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.uni.lu\/en\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Interdisciplinary Centre for Security, Reliability and Trust (SnT)\",\"item\":\"https:\/\/www.uni.lu\/snt-en\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Research projects\",\"item\":\"https:\/\/www.uni.lu\/snt-en\/research-projects\/\"},{\"@type\":\"ListItem\",\"position\":4,\"name\":\"Resource Management in Satellite Communications with Dynamic Topologies: Machine Learning Algorithms for Variable Input-Output Dimensions (ReadyVioSat)\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.uni.lu\/snt-en\/#website\",\"url\":\"https:\/\/www.uni.lu\/snt-en\/\",\"name\":\"SnT\",\"description\":\"Interdisciplinary Centre for Security, Reliability and Trust I Uni.lu\",\"publisher\":{\"@id\":\"https:\/\/www.uni.lu\/snt-en\/#organization\"},\"alternateName\":\"Interdisciplinary Centre for Security, Reliability and Trust I University of Luxembourg\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.uni.lu\/snt-en\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-GB\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/www.uni.lu\/snt-en\/#organization\",\"name\":\"SnT - University of Luxembourg I Uni.lu\",\"alternateName\":\"Interdisciplinary Centre for Security, Reliability and Trust\",\"url\":\"https:\/\/www.uni.lu\/snt-en\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-GB\",\"@id\":\"https:\/\/www.uni.lu\/snt-en\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/03\/03112604\/SNT_SM-Profile_1600x1600px-scaled.jpg\",\"contentUrl\":\"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/03\/03112604\/SNT_SM-Profile_1600x1600px-scaled.jpg\",\"width\":2560,\"height\":2560,\"caption\":\"SnT - University of Luxembourg I Uni.lu\"},\"image\":\"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/04\/24144329\/20200609-Belval-Campus_Henri-Goergen-23.jpg\",\"sameAs\":[\"https:\/\/www.linkedin.com\/school\/snt-lu\/\"],\"email\":\"communication@uni.lu\",\"telephone\":\"+3524666441\",\"address\":{\"@type\":\"PostalAddress\",\"streetAddress\":\"29 Av. John F. Kennedy\",\"addressLocality\":\"Kirchberg\",\"postalCode\":\"1855\",\"addressCountry\":\"LU\"},\"description\":\"Interdisciplinary Centre for Security, Reliability and Trust I Uni.lu\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Resource Management in Satellite Communications with Dynamic Topologies: Machine Learning Algorithms for Variable Input-Output Dimensions (ReadyVioSat) - SnT I University of Luxembourg","description":"As satellite networks become increasingly dynamic and complex, traditional optimisation approaches struggle to keep pace. This project develops advanced machine learning models designed specifically for these evolving environments, enabling networks to adapt to changing conditions while maintaining performance and reliability. The research focuses on creating solutions that are feasible to deploy, adaptable across scenarios, and generalisable to future satellite network architectures.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/","og_locale":"en_GB","og_type":"article","og_title":"Resource Management in Satellite Communications with Dynamic Topologies: Machine Learning Algorithms for Variable Input-Output Dimensions (ReadyVioSat)","og_description":"As satellite networks become increasingly dynamic and complex, traditional optimisation approaches struggle to keep pace. This project develops advanced machine learning models designed specifically for these evolving environments, enabling networks to adapt to changing conditions while maintaining performance and reliability. The research focuses on creating solutions that are feasible to deploy, adaptable across scenarios, and generalisable to future satellite network architectures.","og_url":"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/","og_site_name":"SnT EN","article_modified_time":"2026-06-22T14:18:56+00:00","og_image":[{"width":715,"height":661,"url":"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/06\/22161051\/SnTproject_ReadyVioSat-1.png","type":"image\/png"}],"twitter_card":"summary_large_image","twitter_misc":{"Estimated reading time":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/","url":"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/","name":"Resource Management in Satellite Communications with Dynamic Topologies: Machine Learning Algorithms for Variable Input-Output Dimensions (ReadyVioSat) - SnT I University of Luxembourg","isPartOf":{"@id":"https:\/\/www.uni.lu\/snt-en\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/#primaryimage"},"image":{"@id":"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/#primaryimage"},"thumbnailUrl":"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/06\/22161051\/SnTproject_ReadyVioSat-1.png","datePublished":"2026-06-22T14:18:55+00:00","dateModified":"2026-06-22T14:18:56+00:00","description":"As satellite networks become increasingly dynamic and complex, traditional optimisation approaches struggle to keep pace. This project develops advanced machine learning models designed specifically for these evolving environments, enabling networks to adapt to changing conditions while maintaining performance and reliability. The research focuses on creating solutions that are feasible to deploy, adaptable across scenarios, and generalisable to future satellite network architectures.","breadcrumb":{"@id":"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/#breadcrumb"},"inLanguage":"en-GB","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/"]}]},{"@type":"ImageObject","inLanguage":"en-GB","@id":"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/#primaryimage","url":"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/06\/22161051\/SnTproject_ReadyVioSat-1.png","contentUrl":"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/06\/22161051\/SnTproject_ReadyVioSat-1.png","width":715,"height":661},{"@type":"BreadcrumbList","@id":"https:\/\/www.uni.lu\/snt-en\/research-projects\/resource-management-in-satellite-communications-with-dynamic-topologies-machine-learning-algorithms-for-variable-input-output-dimensions-readyviosat\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.uni.lu\/en"},{"@type":"ListItem","position":2,"name":"Interdisciplinary Centre for Security, Reliability and Trust (SnT)","item":"https:\/\/www.uni.lu\/snt-en\/"},{"@type":"ListItem","position":3,"name":"Research projects","item":"https:\/\/www.uni.lu\/snt-en\/research-projects\/"},{"@type":"ListItem","position":4,"name":"Resource Management in Satellite Communications with Dynamic Topologies: Machine Learning Algorithms for Variable Input-Output Dimensions (ReadyVioSat)"}]},{"@type":"WebSite","@id":"https:\/\/www.uni.lu\/snt-en\/#website","url":"https:\/\/www.uni.lu\/snt-en\/","name":"SnT","description":"Interdisciplinary Centre for Security, Reliability and Trust I Uni.lu","publisher":{"@id":"https:\/\/www.uni.lu\/snt-en\/#organization"},"alternateName":"Interdisciplinary Centre for Security, Reliability and Trust I University of Luxembourg","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.uni.lu\/snt-en\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-GB"},{"@type":"Organization","@id":"https:\/\/www.uni.lu\/snt-en\/#organization","name":"SnT - University of Luxembourg I Uni.lu","alternateName":"Interdisciplinary Centre for Security, Reliability and Trust","url":"https:\/\/www.uni.lu\/snt-en\/","logo":{"@type":"ImageObject","inLanguage":"en-GB","@id":"https:\/\/www.uni.lu\/snt-en\/#\/schema\/logo\/image\/","url":"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/03\/03112604\/SNT_SM-Profile_1600x1600px-scaled.jpg","contentUrl":"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/03\/03112604\/SNT_SM-Profile_1600x1600px-scaled.jpg","width":2560,"height":2560,"caption":"SnT - University of Luxembourg I Uni.lu"},"image":"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/5\/2026\/04\/24144329\/20200609-Belval-Campus_Henri-Goergen-23.jpg","sameAs":["https:\/\/www.linkedin.com\/school\/snt-lu\/"],"email":"communication@uni.lu","telephone":"+3524666441","address":{"@type":"PostalAddress","streetAddress":"29 Av. John F. Kennedy","addressLocality":"Kirchberg","postalCode":"1855","addressCountry":"LU"},"description":"Interdisciplinary Centre for Security, Reliability and Trust I Uni.lu"}]}},"_links":{"self":[{"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/research-projects\/24907"}],"collection":[{"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/research-projects"}],"about":[{"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/types\/research-projects"}],"author":[{"embeddable":true,"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/users\/399"}],"version-history":[{"count":3,"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/research-projects\/24907\/revisions"}],"predecessor-version":[{"id":24910,"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/research-projects\/24907\/revisions\/24910"}],"wp:authorship":[{"embeddable":true,"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/users\/399"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/media\/24905"}],"wp:attachment":[{"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/media?parent=24907"}],"wp:term":[{"taxonomy":"research-project-status","embeddable":true,"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/research-project-status?post=24907"},{"taxonomy":"research-project-type","embeddable":true,"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/research-project-type?post=24907"},{"taxonomy":"field-of-interest","embeddable":true,"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/field-of-interest?post=24907"},{"taxonomy":"organisation","embeddable":true,"href":"https:\/\/www.uni.lu\/snt-en\/wp-json\/wp\/v2\/organisation?post=24907"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}