Universitetet I Agder

Grimstad

<h2>About the position</h2><p>A 100% position is available at the University of Agder, Faculty of the <a href="https://www.uia.no/english/about-uia/faculty/engineering-and-science/index.html" rel="nofollow">Faculty of Engineering and Science</a> as a PhD Research Fellow in ICT, affiliated to the Department of <a href="https://www.uia.no/english/about-uia/faculty/engineering-and-science/ict/index.html" rel="nofollow">Department of Information and Communication Technology</a> at, for a period of three years, or four years with 25% other career-promoting work. The position is located at Campus Grimstad.</p><p>The starting date is negotiable with the Faculty. </p><br /><h2>Responsibilities</h2><p>This PhD position is directly linked to an ongoing Research Council of Norway Innovation Project, F<strong>AI</strong>R - Fast and Accurate Investigation and Response, where UiA is a core research partner. The position is embedded in the <a href="https://www.uia.no/english/research/research-groups/engineering-and-science/cair.html" rel="nofollow">Centre for Artificial Intelligence Research</a> (CAIR) and <a href="https://www.uia.no/english/research/research-groups/social-sciences/ciemfg.html" rel="nofollow">Centre for Integrated Emegency Management</a> (CIEM) and will contribute to cutting-edge research at the intersection of AI, investigation and emergency management. The research will be conducted in realistic, data-intensive environments and will address challenges related to robustness, reliability, evaluation, and trust in AI systems deployed in high-stakes police operational settings.</p><p>The project will be conducted in close collaboration with industry and research partners, including DavidHorn, and will involve applied research in realistic, data-intensive environments.</p><p><strong>Research topics</strong></p><p>The PhD candidate will conduct research on advanced artificial intelligence systems that address core research challenges identified in the project, with a particular focus on search, representation learning, and evaluation in multimodal and temporally structured data. The research will emphasize:</p><ul><li>Multimodal machine learning, developing shared and aligned representations across text, audio, video, and time-series, enabling effective cross-modal search, retrieval, and reasoning</li><li>Embedding-based methods for information extraction, similarity search, and integration of heterogeneous data sources, including investigation of how different modalities contribute to semantic alignment and downstream decision support</li><li>Evaluation and benchmarking of complex AI systems beyond standard text-only benchmarks, with particular emphasis on robustness, temporal consistency, and performance under realistic, high-stakes operating conditions</li><li>Trustworthy AI, including systematic analysis of uncertainty, failure modes, bias, and interpretability in multimodal systems, especially where AI outputs are used to support human decision-making</li></ul><p>Key research themes include:</p><ul><li>Neural architectures for representation learning, search, and reasoning, with emphasis on learning robust and aligned embeddings across heterogeneous modalities (text, audio, video and time-series data) that support retrieval, information integration, and decision support in temporally evolving environments</li><li>Rigorous evaluation, and benchmarking methodologies for AI systems operating in real-world, data-sensitive domains domains, including assessment of robustness, uncertainty, temporal consistency, and degradation under distribution shift, beyond conventional static or text-only benchmarks</li><li>Explainability and interpretability methods tailored to complex multimodal and embedding-based systems, focusing on how model decisions, retrieved evidence, and cross-modal representations can be made transparent and inspectable for expert users</li><li>Research approach combining theory, methods, and empirical experimentation, aligned with client environment, where advances in representation learning and evaluation are validated through controlled experiments.</li><li> realistic pilots in data intensive environment, tailored to the needs of the project client such as AI support for better cooperation between different levels of operational environments. </li><li>Contribute to  high-quality scientific publications and reusable benchmarking and evaluation frameworks</li><li>:Contribute to open and reproducible research practices within CAIR and CIEM</li></ul><p>A prerequisite for employment is that the candidate is to be admitted to <a href="https://www.uia.no/english/studies/programmes/phd-programme-in-engineering-and-science/" rel="nofollow">UiA’s PhD programme at the Faculty of Engineering and Sciences</a>.</p><br /><h2>Required qualifications</h2><ul><li>Master’s degree (completed or near completion) in Computer Science, ICT, Artificial Intelligence, or a closely related field</li><li>Solid foundation in artificial intelligence, machine learning, or computer science, including deep neural networks</li><li>Research-oriented mindset with the ability to reason critically about:</li><li>Model assumptions</li><li>Limitations</li><li>Evaluation and benchmarking methodologies</li></ul><p>Experience with or strong interest in:</p><ul><li>Multimodal AI (text, audio, video, and time-series data)</li><li>Large language models and embedding-based methods</li><li>Explainable and trustworthy AI</li><li>modern machine-learning and data frameworks, and collaborative development workflows</li></ul><p>Strong programming skills, particularly in Python</p><p>Written and spoken English proficiency. International candidates that are not exempt from the English language requirements pursuant to the guidelines of the Norwegian Agency for Quality Assurance in Education (NOKUT) must document this through one of the following tests with the stated results or better: </p><ul><li>TOEFL - Test of English as a Foreign Language with a minimum score of 600 for the Paperbased Test (PBT), or 92 for the Internet-based Test (iBT)</li><li>IELTS - International English Language Testing System, with the result of 6.5 </li></ul><p><a href="https://lovdata.no/forskrift/2024-06-28-1392/§3-19" rel="nofollow">Criteria for positions as PhD Research Fellow</a> (in Norwegian).</p><br /><h2>Desired qualifications</h2><ul><li>Experience or strong interest in: Representation learning and embedding-based search and retrieval, Multimodal and cross-modal information extraction and reasoning and Temporal and sequential data modelling</li><li>Familiarity with: Evaluation and benchmarking of AI systems beyond text-only benchmarks, Robustness, uncertainty estimation, bias analysis, and failure-mode analysis in AI systems and AI systems deployed in high-stakes or data-sensitive operational environments</li><li>Interest in applied AI for investigation, policing, emergency management, or decision support systems</li><li>Prior research experience, such as scientific publications, advanced project work, or industry-facing applied research</li><li> Experience with or interest in open and reproducible research practices</li></ul><br /><h2>Personal qualities</h2><ul><li>Strong motivation to push the boundaries of current AI technology</li><li>Ability to work independently in a structured, goal-oriented manner</li><li>Excellent analytical skills and attention to detail</li><li>Good communication skills and ability to collaborate effectively in interdisciplinary teams</li><li>Inventiveness, curiosity, and a proactive approach to research challenges</li><li>Willingness to engage actively in an international research environment and industry collaboration</li><li>Personal suitability, teamwork skills, and capacity for sustained concentration will be given significant weight</li></ul><br /><h2>We offer</h2><ul><li>professional development in a large, exciting and socially influential organisation </li><li>a positive, inclusive and diverse working environment </li><li>modern facilities and a comprehensive set of welfare offers </li><li>membership of the <a href="https://www.spk.no/en/the-value-of-the-membership/" rel="nofollow">Norwegian Public Service Pension Fund </a></li></ul><p><a href="https://www.uia.no/english/about-uia/working-at-uia/" rel="nofollow">More about working at UiA.</a></p><p>The position is remunerated according to the State Salary Scale, salary plan 17.515, code 1017 PhD Research Fellow, NOK 550 800 gross salary per year. A compulsory pension contribution to the Norwegian Public Service Pension Fund is deducted from the pay according to current statutory provisions.</p><br /><h2>General information</h2><p>UiA is an open and inclusive university. We believe that diversity enriches the workplace and makes us better. We, therefore, encourage qualified candidates to apply for the position independent of gender, age, cultural background, disability or an incomplete CV.</p><p>Women are strongly encouraged to apply for the position. </p><p>The successful applicant will have rights and obligations in accordance with the current regulations for the position, and organisational changes and changes in the duties and responsibilities of the position must be expected. The engagement is to be made in accordance with the regulations in force concerning the acts relating to <a href="https://www.uia.no/english/about-uia/acts-and-regulations/export-control.html" rel="nofollow">Control of Export of Strategic Goods, Services and Technology</a>.</p><p>A background check may be carried out to verify information stated in the CV and available documents. Background checks are not conducted without the applicant&#39;s consent, and relevant applicants will receive further information about this. You can find more information about background checks at UiA here (in Norwegian): <a href="https://www.uia.no/intranett/arbeidsstotte/ansvarlig-internasjonalt-samarbeid/ansvarlighet-i-internasjonale-ansettelser-og-motta.html" rel="nofollow">Ansvarlighet i internasjonale ansettelser og mottak av gjesteforskere - For ansatte</a></p><p>Appointment is made by the University of Agder’s Appointments Committee for Teaching and Research Positions. </p><p>Short-listed applicants will be invited for interview. With the applicant’s permission, UiA will also conduct a reference check before appointment. Read more about the <a href="https://www.uia.no/english/about-uia/working-at-uia/appointment-process.html" rel="nofollow">employment process</a>.</p><p>In accordance with the Freedom of Information Act § 25 (2), applicants may request that they are not identified in the open list of applicants. The University, however, reserves the right to publish the names of applicants. Applicants will be advised of the University’s intention to exercise this right. </p><br /><h2>Application</h2><p>The application and any necessary information about education and experience (including diplomas and certificates) are to be sent electronically. Use the link <strong>&#34;Apply for this job&#34;</strong>.</p><p>The following documentation must be uploaded electronically: </p><ul><li>Certificates with grades</li><li>Master’s thesis</li><li>References</li><li>Academic work and R&amp;D projects, as well as a list of these</li><li>Project description with a maximum scope of x pages, including reference list. The outline should present and discuss possible research questions, theory perspectives, material, a progress plan, and methods within the given framework</li><li>Any other relevant documentation</li></ul><p>The applicant is fully responsible for submitting complete digital documentation before the closing date. All documentation must be available in a Scandinavian language or English. </p><p><strong>Application deadline: 24.02.26</strong></p><br /><h2>Contact</h2><p>For questions about the position: </p><ul><li>Professor Morten Goodwin, tel. &#43;47 37 23 31 05, e-mail <a href="mailto:morten.goodwin&#64;uia.no" rel="nofollow">morten.goodwin&#64;uia.no</a></li><li>Professor Jaziar Radianti, tel. &#43;47 37 23 34 35, e-mail <a href="mailto:jaziar.radianti&#64;uia.no" rel="nofollow">jaziar.radianti&#64;uia.no</a> </li><li>Head of Department Folke Haugland, tel. &#43;47 37 23 32 20, e-mail <a href="mailto:folke.haugland&#64;uia.no" rel="nofollow">folke.haugland&#64;uia.no</a> </li></ul><p>For questions about the application process:</p><ul><li>HR-advisor, Linda H. Kristiansen, tel. &#43;47 38 14 11 88, e-mail <a href="mailto:linda.h.kristiansen&#64;uia.no" rel="nofollow">linda.h.kristiansen&#64;uia.no</a></li></ul><br /><h2>Creating knowledge together</h2><p>When people who are committed come together to further knowledge, anything is possible.</p><p>The University of Agder combines the unique warmth and charm of Southern Norway with first-class scientific, technological and artistic expertise.</p><p>Would you like to work with us to create better solutions to our shared challenges?</p>Video: <a href="https://vimeo.com/782451416/773266e83a" rel="nofollow">https://vimeo.com/782451416/773266e83a</a>

PhD Research Fellow in ICT: Multimodal AI for Fast and Accurate Investigation and Response