Universitetet i Oslo

Oslo

Thoril Kristiansen

Senior HR Adviser

Victor Greiff

Professor

<h2>Job description</h2><p>Applications are invited for a 3-year position in a Research Fellowship as PhD Candidate in immunology (computational biology) to be based at the Department of Immunology, Division of Laboratory Medicine, Institute of Clinical Medicine, University of Oslo.</p> <p>The position is available from October 2025 with a flexible start between October 2025 and April 2026. The position will be located in the laboratory of Dr. Greiff (Lab for Computational and Systems Immunology, greifflab.org). The position is funded by a HORIZON-MSCA-2024-DN (Transcend).</p><br /><h2>More about the position / Project description</h2><p>The candidate will develop and employ a variety of computational biology techniques to perform antibody design both on the sequence and structural level, developing and employing machine-learning tools for predicting antibody-epitope binding. In silico antibody design is a long-standing computational and immunological problem. Improving computational methods for antibody recognition is crucial for the development of personalized and precision medicine approaches such as next-generation infection, cancer, and autoimmune immunodiagnostics and immunotherapeutics. The candidate will be expected to closely collaborate with machine learning experts, statisticians, computational and experimental immunologists, as well as clinicians.</p><p>The Greiff Lab focuses on the quantitative understanding of adaptive immune receptor (antibody and T-cell receptor) specificity using high-throughput experimental and computational immunology combined with machine learning. The long-term aim is to conceive in-silico novel immunodiagnostics and immunotherapeutics using the disease-diagnostic information and therapeutic potential that is directly encoded into adaptive immune receptors. The advent of high-throughput sequencing has enabled an unprecedented accumulation of big immune repertoire sequencing data. However, as of yet, we lack the computational methods that help us decode the immune grammar that translates immune sequencing data to immune state diagnosis and prediction of antigen binding. We believe that learning to read and write the immune repertoire language is key for the development of entirely novel, nature-inspired precision medicine immunodiagnostics and immunotherapeutics. Recent publications by Dr. Greiff may be found on<a href="https://scholar.google.ch/citations?user&#61;7ibUgaEAAAAJ&amp;hl&#61;en" rel="nofollow"> google scholar</a>.</p><br /><h2>Qualification requirements</h2><ul><li>Applicants must hold a Master’s degree (120 ECTS) or equivalent in Statistics, Computer Science, Mathematics, Computational Biology or related field, minimum grade B (ECTS grading scale) or equivalent. The Master’s degree must include a thesis of at least 30 ECTS.</li><li>Experience in computational biology is an advantage.</li><li>Experience in structural biology is an advantage.</li><li>Experience in immune receptor immunology is an advantage.</li></ul> <ul><li>Experience in high-performance parallel computing is an advantage.</li><li>Experience with machine learning and or other mathematical approaches used in (bulk and single-cell) immune repertoire analysis is considered an advantage.</li><li>Experience in statistical physics is an advantage</li><li>Fluent oral and written communication skills in English.</li></ul><br /><h2>Personal skills</h2><p>The candidate will work in a very ambitious interdisciplinary setting which will require high flexibility, good communication and collaboration skills.</p><p>Employment in the position is based on a comprehensive assessment of all qualification requirements applicable to the position, including personal qualifications.</p><br /><h2>We offer</h2><ul><li>Exciting and meaningful tasks in an organization with an important societal mission, contributing to knowledge development, education, and enlightenment that promote sustainable, fair, and knowledge-based societal development.</li><li>Committed colleagues in a good working environment. </li><li>Good <a href="https://www.uio.no/english/for-employees/employment/welfare/index.html" rel="nofollow">welfare schemes.</a></li><li>Opportunity of up to 1.5 hours a week of <a href="https://www.uio.no/english/for-employees/employment/welfare/exercise/" rel="nofollow">exercise during working hours.</a></li><li>A workplace with good development and career opportunities. </li><li>Membership in the <a href="https://www.spk.no/en/" rel="nofollow">Statens Pensjonskasse</a>, which is one of Norway&#39;s best pension schemes with beneficial mortgages and good insurance schemes.</li><li>Salary in position as Doctoral Research Fellow, position code 1017 in salary range from NOK 551 000 - NOK 594 000, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund.</li></ul><p>Read more about the benefits of working in the public sector at <a href="http://arbeidsgiver.difi.no/lonn-goder-og-reise" rel="nofollow">Employer Portal</a>.</p><br /><h2>Inclusive worklife and diversity at UiO</h2><p>Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience and perspectives.</p><p>If there are qualified applicants with disabilities, employment gaps or immigrant background, we will invite at least one applicant from each of these categories to an interview.</p><p>We hope that you will apply for the position. </p><p>More information about gender equality initiatives at UiO can be found <a href="https://www.uio.no/english/for-employees/competence/gender-equality/index.html" rel="nofollow">here.</a></p><br /><h2>Application</h2><p>Your application should include:</p><ul><li>Application letter.</li><li>CV.</li><li>A complete list of publications.</li><li>Transcripts and certificates.</li><li>Contact information for 2-3 references.</li></ul><p>Application with attachments must be submitted via our recruitment system Jobbnorge, click &#34;Apply for the position&#34;.</p><p>When applying for the position, we ask you to retrieve your education results from <a href="https://www.vitnemalsportalen.no/english/" rel="nofollow">Vitnemålsportalen.no</a>. If your education results are not available through Vitnemålsportalen, we ask you to upload copies of your transcripts or grades. Please note that all documentation must be in English or a Scandinavian language.</p><br /><h2>General information</h2><p>The best qualified candidates will invited for interviews. </p><p>Applicant lists can be published in accordance with <a href="https://lovdata.no/dokument/NLE/lov/2006-05-19-16" rel="nofollow">Norwegian Freedom of Information Act</a> § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we cannot, you will hear from us.</p> <p>Please refer to <a href="https://lovdata.no/dokument/SF/forskrift/2024-06-28-1392/KAPITTEL_3#KAPITTEL_3" rel="nofollow">Regulations for the Act on universities and colleges chapter 3</a> (Norwegian),  <a href="https://www.uio.no/english/about/regulations/personnel/academic/guidelines-appointment-postdoc-researcher.html" rel="nofollow">Guidelines concerning appointment to post doctoral and research posts at UiO</a> and <a href="https://www.uio.no/english/about/regulations/research/doctoral-degree/phdforskreng.html" rel="nofollow">Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo.</a></p><p>The University of Oslo has a <a href="https://www.uio.no/english/for-employees/employment/work-results/agreement-rights-to-work-results.html" rel="nofollow">transfer agreement</a> with all employees that is intended to secure the rights to all research results etc.</p><br />

PhD Fellowship in Computational Systems Immunology