InstitutionCluster of Excellence "Understanding Written Artefacts"Salary levelEGR. 13 TV-LStart date, fixed until This is a fixed-term contract in accordance with Section 2 of the academic fixed-term labor contract act (Wissenschaftszeitvertragsgesetz, WissZeitVG)).Application deadline Scope of workfull-time position suitable for part-timeThe Cluster of Excellence 'Understanding Written Artefacts' (UWA) is looking for adoctoral researcherin the field ofComputer Sciencefor theVisual Manuscript Analysis Lab (VMA). UWA offers an exciting opportunity to research handwritten artefacts across materials, periods and regions within a collaborative team of doctoral, postdoctoral and senior/professorial researchers. You will be part of an international team of researchers from across over forty disciplines in the Humanities, the Natural Sciences and Computer Science. The Centre for the Study of Manuscript Cultures is by now the largest research centre of its kind worldwide and offers a uniquely dynamic research environment.Your responsibilitiesDuties include academic services in the project named above. Research associates may also pursue independent research and further academic qualifications. They may also pursue doctoral studies outside of working duties.Your core responsibility is to pursue your research project, involving to design, implement, and evaluate machine learning approaches relevant to the project's objectives. You will contribute to the research activities of the VMA lab, including meetings, seminars, and collaborative projects within the cluster UWA. Eventually, you will be a part of the cluster's Graduate School and participate actively in its colloquia and collaborative research networks.Your profileA university degree in a relevant field.Fluent English, written and spoken.A university degree (Master or equivalent) in computer science, artificial intelligence, data science, or a closely related discipline is preferred. You have strong theoretical and practical knowledge of machine learning, as well as foundational understanding of computer vision and vision–language learning, including familiarity with relevant software packages and libraries. A demonstrable ability to implement state-of-the-art machine learning methods, evidenced by, for example, publicly accessible code repositories, is desirable.Further Preferred Qualifications And Experience Includeresearch or project experience in computer vision approachesfamiliarity with natural language processingpractical experience with vision–language models, such as CLIP and InstructBLIPWe offerReliable remuneration based on wage agreementsContinuing education opportunitiesUniversity pensionsAttractive locationFlexible working hoursWork-life balance opportunitiesHealth management, EGYM WellpassEducational leave30 days of vacation per annumThe successful candidate can benefit from a range of tailored support measures at the Cluster, which include,enrolment in the clusters Graduate School with an interdisciplinary structured PhD programmeadditional funding for a range of research activities, including fieldworkdoctoral mentoring programmesworkshops to support your academic skills as well as your career planningpromoting equity and diversityUniversität Hamburg—University of Excellence is one of the strongest research educational institutions in Germany. Our work in research, teaching, educational and knowledge exchange activities is fostering the next generation of responsible global citizens ready to tackle the global challenges facing us. Our guiding principle "Innovating and Cooperating for a Sustainable Future in a digital age" drives collaboration with academic and nonacademic partner institutions in the Hamburg Metropolitan Region and around the world. We would like to invite you to be part of our community to work with us in creating sustainable and digital change for a dynamic and pluralist society.The University of Hamburg is committed to equity. Diversity enriches our university life, whether in our studies, research, teaching, education, or workplace. We therefore welcome all applications, regardless of gender, gender identity, sexual orientation, ethnic or social background, age, religion or belief, disability, or chronic illness.Severely disabled and disabled applicants with the same status will receive preference over equally qualified non-disabled applicants.Instructions for applyingContactDr. rer. nat. Hussein MohammedReference number235LocationWarburgstraße 26-2822354 HamburgZu Google MapsApplication deadline Use only the online application form to submit your application with the following documents:cover letterCVcopies of degree certificate(s)If you experience technical problems, send an email to -More information on data protection in selection procedures.PDF Downloadapply