{"data":{"id":219106,"slug":"postdoktor-inom-probabilistiska-metoder-for-foundation-och-world-modeller","type":"job","title":"Postdoctoral Researcher in Probabilistic Methods for Foundation and World Models","description":"Would you like to work with probabilistic machine learning for the next generation of AI models in an international environment with competent and pleasant colleagues? We welcome your application for a postdoctoral position at Uppsala University.\nThis is an abbreviated version of the job posting. The complete posting is available on Uppsala University's website, uu.se\/jobb.\nThe Department of Information Technology is Uppsala University's third-largest department with over 350 employees and participates in the Wallenberg AI, Autonomous Systems and Software Program (WASP). More information is available on the department's website.\nThe position is located at the Division of Scientific Computing (TDB), one of the world's largest research environments in scientific computing and an important part of the e-science collaboration eSSENCE and Science for Life Laboratory (SciLifeLab), a national research infrastructure for life sciences.\nYou will join the Scientific Machine Learning research group at TDB and SciLifeLab. The group develops theory, methods, and software for data-driven science, with a focus on uncertainty quantification in large pre-trained models, generative models, simulation-based inference, and robust and active learning.\nProject Description\nThe position offers significant scientific freedom within the theme of probabilistic methods for foundation models and world models: making them uncertainty-aware, calibrated, robust, and useful for scientific decision-making. You may build on one of the following areas or propose your own topic within the theme (describe your research direction, max 2 pages): Uncertainty quantification, calibration, and reliability in large pre-trained models. Probabilistic generative models and world models. Probabilistic machine learning for scientific discovery.\nMotivating applications exist in the life sciences, where the group collaborates through SciLifeLab in areas such as microscopy, drug development, and precision medicine, with access to real, large-scale, and multimodal data. The emphasis is on high-quality fundamental AI\/ML methodological contributions that applications can benefit from.\nDuties\nResearch, publishing and conference presentations, contributions to the group's open-source software, and participation in student supervision. A limited amount of teaching may be included (maximum 20%).\nQualifications\nA doctoral degree in machine learning, computer science, computational science, mathematics, statistics, or a closely related field, or a foreign degree assessed as equivalent to a doctoral degree in one of these areas. The degree must be completed by the time the employment decision is made. Preferably, the degree should have been obtained no more than three years ago. When calculating the three-year period, the starting point is the final application deadline. If there are special reasons, such a degree may have been obtained earlier. Special reasons include leave due to illness, parental leave, positions of trust within trade union organizations, etc.\nDocumented research experience with modern deep learning and very good programming skills in Python and a modern deep learning framework (e.g., PyTorch or JAX) are required. Good knowledge of English in speech and writing is required. Candidates must clearly demonstrate a high degree of self-motivation in their application. Great weight is placed on personal qualities such as creativity, accuracy, a structured approach, and the ability to work both independently and in a team.\nDesirable\/Meritorious Experience\nPublications at leading machine learning or computer vision conferences (NeurIPS, ICML, ICLR, CVPR, etc.) are strongly meritorious. Expertise in Bayesian methods, generative models, multimodal models, world models, or simulation-based inference is meritorious, as is experience with large-scale training on GPU clusters, open-source software development, and applications in the life sciences.\nTeaching experience is meritorious but not required. Teaching experience may include, for example, instruction, supervision, mentoring, work as a teaching assistant, internal training, or other educational activities, within or outside higher education. Particular weight is placed on activities that support students' learning in computer science, information technology, or related subjects.\nApplication\nYour application must include:\nA curriculum vitae (CV),\nA copy of relevant grade documents (translated into Swedish or English),\nA list of publications,\nUp to five selected publications in electronic format,\nA research description describing your previous and current research (max 1 page) and a proposal for future activities (max 1 page),\nContact information for two references,\n\nAbout the Position\nThe position is time-limited for two years according to central collective agreement. The position is full-time. Start date: November 1, 2026 or by agreement. Work location: Uppsala\nInformation about the position is provided by: University Lecturer Prashant Singh, prashant.singh@scilifelab.uu.se; Division Head Elisabeth Larsson, elisabeth.larsson@it.uu.se.\nIn this recruitment, we have replaced the cover letter with questions that you answer as part of your application. The answers will be used as part of the selection process.\nWelcome to submit your application by Thursday, October 15, 2026, UFV-PA 2026\/2764\nUppsala University is a broad research university with a strong international position. The ultimate goal is to conduct education and research of the highest quality and relevance to make a difference in society. Our most important asset is all 7,500 employees and 53,000 students who with curiosity and commitment make Uppsala University one of the country's most exciting workplaces.\nRead more about our benefits and what it's like to work at Uppsala University\nhttps:\/\/uu.se\/om-uu\/jobba-hos-oss\/\nThe position may be subject to security clearance. For security clearance to be conducted, it is a requirement for employment that the applicant is approved.\nWe decline offers of recruitment and advertising assistance.\nApplications are received through Uppsala University's recruitment system.\nTrade union representatives: Saco-S - saco-s@uu.se, Seko - seko@uadm.uu.se, ST (OFR\/S) - ofr@uu.se","language":"sv","is_translated":true,"title_original":"Postdoktor inom probabilistiska metoder f\u00f6r foundation och world modeller","description_original":"Vill du arbeta med probabilistisk maskininl\u00e4rning f\u00f6r n\u00e4sta generations AI-modeller i en internationell milj\u00f6 med kompetenta och trevliga kollegor? V\u00e4lkommen att s\u00f6ka anst\u00e4llning som postdoktor p\u00e5 Uppsala universitet.\nDetta \u00e4r en f\u00f6rkortad version av annonsen. Den fullst\u00e4ndiga annonsen finns p\u00e5 Uppsala universitets webbplats, uu.se\/jobb.\nInstitutionen f\u00f6r informationsteknologi \u00e4r Uppsala universitets tredje st\u00f6rsta institution med drygt 350 anst\u00e4llda och deltar i Wallenberg AI, Autonomous Systems and Software Program (WASP). Mer information finns p\u00e5 institutionens webbplats.\nAnst\u00e4llningen \u00e4r placerad vid avdelningen f\u00f6r ber\u00e4kningsvetenskap (TDB), en av v\u00e4rldens st\u00f6rsta forskningsmilj\u00f6er inom ber\u00e4kningsvetenskap och en viktig del av e-vetenskapssamarbetet eSSENCE och av Science for Life Laboratory (SciLifeLab), en nationell forskningsinfrastruktur f\u00f6r livsvetenskaperna.\nDu kommer att ing\u00e5 i forskargruppen Scientific Machine Learning vid TDB och SciLifeLab. Gruppen utvecklar teori, metoder och programvara f\u00f6r datadriven vetenskap, med fokus p\u00e5 os\u00e4kerhetskvantifiering i stora f\u00f6rtr\u00e4nade modeller, generativa modeller, simuleringsbaserad inferens samt robust och aktiv inl\u00e4rning.\nProjektbeskrivningAnst\u00e4llningen erbjuder stor vetenskaplig frihet inom temat probabilistiska metoder f\u00f6r foundation-modeller och world models: att g\u00f6ra dem os\u00e4kerhetsmedvetna, kalibrerade, robusta och anv\u00e4ndbara f\u00f6r vetenskapligt beslutsfattande. Du kan utg\u00e5 fr\u00e5n n\u00e5got av f\u00f6ljande eller f\u00f6resl\u00e5 ett eget \u00e4mne inom temat (beskriv din forskningsinriktning, max 2 sidor): Os\u00e4kerhetskvantifiering, kalibrering och tillf\u00f6rlitlighet i stora f\u00f6rtr\u00e4nade modeller. Probabilistiska generativa modeller och world models. Probabilistisk maskininl\u00e4rning f\u00f6r vetenskaplig uppt\u00e4ckt.\nMotiverande till\u00e4mpningar finns inom livsvetenskaperna, d\u00e4r gruppen via SciLifeLab samarbetar inom bl.a. mikroskopi, l\u00e4kemedelsutveckling och precisionsmedicin, med tillg\u00e5ng till verkliga, storskaliga och multimodala data. Tyngdpunkten ligger p\u00e5 grundl\u00e4ggande AI\/ML-metodbidrag av h\u00f6g kvalitet, som till\u00e4mpningarna kan dra nytta av.\nArbetsuppgifterForskning, publicering och konferenspresentationer, bidrag till gruppens \u00f6ppna programvara samt medverkan i handledning av studenter. En begr\u00e4nsad andel undervisning kan ing\u00e5 (h\u00f6gst 20 %).\nKvalifikationskravDoktorsexamen i maskininl\u00e4rning, datavetenskap, ber\u00e4kningsvetenskap, matematik, statistik eller ett n\u00e4rliggande omr\u00e5de, eller en utl\u00e4ndsk examen som bed\u00f6ms motsvara doktorsexamen inom n\u00e5got av dessa omr\u00e5den. Examen ska vara uppfyllt senast vid tidpunkten d\u00e5 anst\u00e4llningsbeslutet fattas. Fr\u00e4mst b\u00f6r den komma ifr\u00e5ga som har avlagt examen f\u00f6r h\u00f6gst tre \u00e5r sedan. Vid ber\u00e4kning av ramtiden om tre \u00e5r \u00e4r utg\u00e5ngspunkten sista ans\u00f6kningsdag. Om det finns s\u00e4rskilda sk\u00e4l kan s\u00e5dan examen ha avlagts tidigare. Med s\u00e4rskilda sk\u00e4l avses ledighet p\u00e5 grund av sjukdom, f\u00f6r\u00e4ldraledighet, f\u00f6rtroendeuppdrag inom fackliga organisationer, etc.\nDokumenterad forskningserfarenhet av modern djupinl\u00e4rning samt mycket goda programmeringskunskaper i Python och ett modernt djupinl\u00e4rningsramverk (t.ex. PyTorch eller JAX) kr\u00e4vs. Goda kunskaper i engelska i tal och skrift kr\u00e4vs. Kandidaten ska tydligt dokumentera en h\u00f6g grad av sj\u00e4lvmotivation i ans\u00f6kan. Stor vikt l\u00e4ggs vid personliga egenskaper s\u00e5som kreativitet, noggrannhet, ett strukturerat arbetss\u00e4tt samt f\u00f6rm\u00e5ga att arbeta b\u00e5de sj\u00e4lvst\u00e4ndigt och i team.\n\u00d6nskv\u00e4rt\/meriterande i \u00f6vrigtPublikationer vid ledande maskininl\u00e4rnings- eller datorseendekonferenser (NeurIPS, ICML, ICLR, CVPR etc.) \u00e4r starkt meriterande. Expertis inom Bayesianska metoder, generativa modeller, multimodala modeller, world models eller simuleringsbaserad inferens \u00e4r meriterande, liksom erfarenhet av storskalig tr\u00e4ning p\u00e5 GPU-kluster, \u00f6ppen programvaruutveckling och till\u00e4mpningar inom livsvetenskaperna.\nUndervisningserfarenhet \u00e4r meriterande men inte ett krav. Undervisningserfarenhet kan omfatta t.ex. undervisning, handledning, mentorskap, arbete som hj\u00e4lpl\u00e4rare, internutbildning eller andra pedagogiska aktiviteter, inom eller utanf\u00f6r h\u00f6gre utbildning. S\u00e4rskild vikt l\u00e4ggs vid aktiviteter som st\u00f6djer studenters l\u00e4rande inom datavetenskap, informationsteknologi eller n\u00e4rliggande \u00e4mnen.\nAns\u00f6kanAns\u00f6kan m\u00e5ste inneh\u00e5lla:\nEtt curriculum vitae (CV),\nEn kopia av relevanta betygsdokument (\u00f6versatta till svenska eller engelska),\nEn publikationslista,\nUpp till fem utvalda publikationer i elektroniskt format,\nEn forskningsbeskrivning som beskriver din tidigare och nuvarande forskning (max 1 sida) och ett f\u00f6rslag till framtida aktiviteter (max 1 sida),\nKontaktinformation f\u00f6r tv\u00e5 referenser,\n\nOm anst\u00e4llningen\nAnst\u00e4llningen \u00e4r tidsbegr\u00e4nsad i tv\u00e5 \u00e5r enligt centralt kollektivavtal. Omfattningen \u00e4r heltid. Tilltr\u00e4de 1 november 2026 eller enligt \u00f6verenskommelse. Placeringsort: Uppsala\nUpplysningar om anst\u00e4llningen l\u00e4mnas av: Universitetslektor Prashant Singh, prashant.singh@scilifelab.uu.se; Avdelningsf\u00f6rest\u00e5ndare Elisabeth Larsson, elisabeth.larsson@it.uu.se.\nI denna rekrytering har vi ersatt det personliga brevet med fr\u00e5gor som du besvarar i samband med din ans\u00f6kan. Svaren kommer att anv\u00e4ndas som en del i urvalsprocessen.\nV\u00e4lkommen med din ans\u00f6kan senast torsdagen 15 oktober 2026, UFV-PA 2026\/2764\nUppsala universitet \u00e4r ett brett forskningsuniversitet med stark internationell st\u00e4llning. Det yttersta m\u00e5let \u00e4r att bedriva utbildning och forskning av h\u00f6gsta kvalitet och relevans f\u00f6r att g\u00f6ra skillnad i samh\u00e4llet. V\u00e5r viktigaste tillg\u00e5ng \u00e4r alla 7 500 anst\u00e4llda och 53 000 studenter som med nyfikenhet och engagemang g\u00f6r Uppsala universitet till en av landets mest sp\u00e4nnande arbetsplatser.\nL\u00e4s mer om v\u00e5ra f\u00f6rm\u00e5ner och hur det \u00e4r att jobba inom Uppsala universitet\nhttps:\/\/uu.se\/om-uu\/jobba-hos-oss\/\nAnst\u00e4llningen kan komma att s\u00e4kerhetspr\u00f6vas. Vid s\u00e4kerhetspr\u00f6vning \u00e4r en f\u00f6ruts\u00e4ttning f\u00f6r anst\u00e4llning att s\u00f6kande blir godk\u00e4nd.\nVi undanber oss erbjudanden om rekryterings- och annonseringshj\u00e4lp.\nAns\u00f6kan tas emot i Uppsala universitets rekryteringssystem.\nFackliga f\u00f6retr\u00e4dare: Saco-S - saco-s@uu.se, Seko - seko@uadm.uu.se, ST (OFR\/S) - ofr@uu.se","available_locales":["en"],"price":null,"currency":"SEK","status":"active","noindex":true,"location":{"address":"box 256","full_address":null,"city":"Uppsala","country":"SE","latitude":59.8710738,"longitude":17.5946002},"metadata":{"region":"Uppsala l\u00e4n","duration":"6 m\u00e5nader eller l\u00e4ngre","employer":"Uppsala Universitet","postcode":"75200","positions":1,"profession":"Postdoktor\/Postdoc","salary_type":"Fast m\u00e5nads- vecko- eller timl\u00f6n","employer_url":"http:\/\/www.uu.se\/jobb\/","scope_of_work":"100\u2013100 %","working_hours":"Heltid","employment_type":"full_time","occupation_field":"Pedagogik","employer_workplace":"Uppsala universitet,Institutionen f\u00f6r informationsteknologi","experience_required":true,"employment_type_label":"Vanlig anst\u00e4llning"},"user_id":null,"is_sponsored":false,"views_count":0,"ai_views_count":3,"bot_views_count":0,"ai_vendor_counts":{"openai":2,"anthropic":1},"visibility":"public","submission_source":null,"submission_ai_name":null,"has_owner_email":true,"can_contact_owner":true,"phone":null,"owner_email":"prashant.singh@scilifelab.uu.se","images":[],"published_at":"2026-09-17T10:54:17+00:00","expires_at":"2026-10-15T23:59:59+00:00","created_at":"2026-09-18T04:13:36+00:00","updated_at":"2026-09-22T03:03:17+00:00"}}