{"id":164328,"date":"2025-12-19T03:00:17","date_gmt":"2025-12-19T02:00:17","guid":{"rendered":"https:\/\/www.cde.ual.es\/?p=164328"},"modified":"2025-12-18T14:57:07","modified_gmt":"2025-12-18T13:57:07","slug":"phd-radar-tracking-with-ai-norway","status":"publish","type":"post","link":"https:\/\/www.cde.ual.es\/en\/phd-radar-tracking-with-ai-norway\/","title":{"rendered":"PhD &#8211; Radar tracking with AI &#8211; Norway"},"content":{"rendered":"<p><img decoding=\"async\" class=\"aligncenter\" src=\"https:\/\/www.cde.ual.es\/wp-content\/uploads\/2025\/01\/army-recruit-examines-satellite-reconnaissance-system-world-map-scaled.jpg\" width=\"407\" height=\"271\" \/><\/p>\n<p style=\"text-align: justify;\">The PhD research project is part of the new Norwegian Maritime AI Centre, led by NTNU.<\/p>\n<p style=\"text-align: justify;\">The objective of this PhD project is to develop learning-based methods for maritime tracking and prediction in time- and safety-critical applications. Artificial intelligence techniques will be utilized in order to improve detection capabilities, target recognition and shape estimation, data association, as well as intention prediction, beyond the state of the art. \u00a0In order to support machine learning, the project will make use of historical radar recordings from several vessels as training data. The project will also study how state-of-the-art radar tracking can be used to record additional training data in an efficient and automatic manner, and how simulations can support data augmentation. Key deliverables of this project will be a multi-target radar tracker that learns to utilize radar targets\u2019 amplitude signatures for data association and state estimation, and learning-based prediction models that anticipate the future motion of vessels seen in the radar data, based on the radar data, local geography and historical patterns. The methods are to implemented and verified in real-time using dedicated hardware such as graphical processing units. The PhD candidate will interact with other PhD candidates, researchers, companies and governmental agencies in the center. Together you will pursue different applications and explore different AI methodologies.<\/p>\n<p style=\"text-align: justify;\"><strong>Requirements<\/strong><\/p>\n<ul style=\"text-align: justify;\">\n<li>You must have an academically relevant background such as for example engineering cybernetics, control engineering, machine learning, statistics, informatics, mechanical engineering, or maritime technology.<\/li>\n<li>You must have a Master&#8217;s degree in engineering, informatics, or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained at master&#8217;s level. Master&#8217;s students can apply, but the master&#8217;s degree must be obtained and documented before starting the position and no later than September 2026.<\/li>\n<li>You must have strong academic results from your previous studies and have an average grade from your Master&#8217;s degree study, or equivalent education, which is equal to B or better compared to\u00a0NTNU&#8217;s grading scale. If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have a weaker grade background, you may be considered if you can document that you are particularly suitable for a PhD education.<\/li>\n<li>You must meet the requirements for admission to the faculty&#8217;s Doctoral Program<\/li>\n<li>The person hired must be eligible for security clearance at level CONFIDENTIAL in Norway.<\/li>\n<li>If your native language is not English or Scandinavian, you need to have documentation of your English language skills, e.g. TOEFL.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><strong>Benefits<\/strong><\/p>\n<ul style=\"text-align: justify;\">\n<li>An exciting job with an important\u00a0mission\u00a0in society<\/li>\n<li>Developing tasks in a strong and international professional environment<\/li>\n<li>Career guidance and\u00a0follow-up during the PhD period<\/li>\n<li>Open and inclusive working environment with committed colleagues<\/li>\n<li>Working capital\u00a0that can be used to implement the project<\/li>\n<li>Mentor programme\u00a0as a\u00a0new employee at NTNU<\/li>\n<li>Training during working hours\u00a0and\u00a0company sports at NTNU<\/li>\n<li>As a public employee, you have favourable benefits as a member of the\u00a0Norwegian Public Service Pension Fund (SPK)<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">In the position of PhD Candidate, code 1017, your gross salary will normally be NOK 550 800,- per annum depending on qualifications and seniority. A 2% statutory contribution to the State Pension Fund is deducted from the salary.<\/p>\n<p style=\"text-align: justify;\">The employment period is 3 years.<\/p>\n<p style=\"text-align: justify;\"><b>Organisation\/Company<\/b> \u2013NTNU Norwegian University of Science and Technology.<\/p>\n<p style=\"text-align: justify;\"><b>Field of research<\/b> \u2013 Engineering \u00bb Electrical engineering<\/p>\n<div style=\"text-align: justify;\">Engineering \u00bb Control engineering<\/div>\n<div style=\"text-align: justify;\">Mathematics \u00bb Applied mathematics<\/div>\n<div style=\"text-align: justify;\">Computer science \u00bb Cybernetics<\/div>\n<p style=\"text-align: justify;\"><b>Research profile<\/b>\u00a0\u2013 First Stage Researcher (R1).<\/p>\n<p style=\"text-align: justify;\"><b>Country<\/b>\u00a0\u2013 Norway.<\/p>\n<p style=\"text-align: justify;\"><b>Application deadline<\/b> \u2013 10 Jan 2026 &#8211; 23:59 (Europe\/Oslo).<\/p>\n<p style=\"text-align: justify;\"><strong>More information:\u00a0<a href=\"https:\/\/euraxess.ec.europa.eu\/jobs\/395080\">Euraxess<\/a><\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The PhD research project is part of the new Norwegian Maritime AI Centre, led by NTNU. The objective of this PhD project is to develop learning-based methods for maritime tracking and prediction in time- and safety-critical applications. Artificial intelligence techniques will be utilized in order to improve detection capabilities, target recognition and shape estimation, data [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":156572,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","footnotes":""},"categories":[4048,366,4043],"tags":[407,16707,719,14178,848,938,784,460,16778],"class_list":{"0":"post-164328","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-engineering-architecture","8":"category-eu-calls-and-awards","9":"category-euraxess-en","10":"tag-artificial-intelligence","11":"tag-computer-sciences","12":"tag-engineering","13":"tag-eu-calls","14":"tag-euraxess-en","15":"tag-mathematics","16":"tag-norway","17":"tag-phd","18":"tag-radar-tracking","19":"entry"},"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>PhD - Radar tracking with AI - Norway | CDE Almer\u00eda - Centro de Documentaci\u00f3n Europea - Universidad de Almer\u00eda<\/title>\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.cde.ual.es\/?p=164331\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"PhD - Radar tracking with AI - Norway | CDE Almer\u00eda - Centro de Documentaci\u00f3n Europea - Universidad de Almer\u00eda\" \/>\n<meta property=\"og:description\" content=\"The PhD research project is part of the new Norwegian Maritime AI Centre, led by NTNU. 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