{"data":{"id":228175,"slug":"doktorand-i-maskininlarning-2","type":"job","title":"PhD Student in Machine Learning","description":"Please note that this is a shortened version of the job listing. To see the full listing, please click on \"Apply here\" or visit Uppsala University's website for job openings: https:\/\/www.uu.se\/om-uu\/jobba-hos-oss\/lediga-jobb\nAre you interested in probability theory, statistics, and mathematical modeling? Do you want to develop new methods for uncertainty quantification and apply these methods to large-scale clinical cancer data? Are you looking for an employer that invests in sustainable employee relationships and offers secure, favorable working conditions? You are welcome to apply for a position as a PhD student at the Department of Information Technology at Uppsala University.\nAbout the DDLS Research Program\nThe PhD position is part of the national research program DDLS.\nData-driven life science (DDLS) uses data, computational methods, and artificial intelligence to study biological systems and processes at all levels \u2013 from molecular structures and cellular processes to human health and global ecosystems. SciLifeLab and the Wallenberg National Program for Data-Driven Life Science (DDLS) aim to recruit and educate the next generation of data-driven life science researchers and to create globally leading expertise in computational and data science in Sweden. The program is funded with a total of 3.3 billion kronor over 12 years by the Knut and Alice Wallenberg Foundation (KAW).\nIn 2026, the DDLS research school will expand by recruiting 25 academic and 7 industry PhD students. During the program, more than 260 PhD students and 200 postdoctoral researchers will be part of the research school. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biological diversity, precision medicine and diagnostics, and epidemiology and infectious disease biology. For more information, see: https:\/\/www.scilifelab.se\/data-driven\/ddls-research-school\/\nThe future of life science is data-driven. Do you want to be part of this transformation? Then you are welcome to participate in this unique program!\nUppsala University is now announcing a PhD position within DDLS with a focus on data-driven precision medicine and diagnostics.\nData-driven precision medicine and diagnostics encompass data integration, analysis, visualization, and interpretation of data for patient stratification, discovery of biomarkers for disease risk, diagnostics, drug response, and health monitoring. Research in precision medicine is expected to utilize existing strong resources in Sweden and internationally, such as molecular data (e.g., omics data), imaging data, electronic health records, longitudinal patient and population registers, and biobanks.\nProject Description\nData-driven mathematical and statistical models are increasingly used in life science research and healthcare. Quantifying the uncertainty in these models is crucial for understanding their reliability and for making well-founded decisions based on their predictions. This project aims to develop new methods for uncertainty quantification in mathematical and statistical models. The methods will be applied to large-scale clinical cancer data. A key application will be to quantify the uncertainty in information extracted from medical reports and to propagate this uncertainty into probabilistic models that predict time to event.\nWork Tasks\nThe PhD student will primarily focus on their own research education. Other duties at the department, such as teaching and administrative work, may be included within the scope of employment (max 20%).\nQualification Requirements\nBasic eligibility for studies at the research level is held by those who:\nhave completed a degree at advanced level in applied mathematics, applied statistics, engineering physics, physics, machine learning, or in a similar field, or\nhave completed at least 240 higher education credits, of which at least 60 higher education credits at advanced level including an independent work of at least 15 higher education credits, or\nin some other way within or outside the country have acquired essentially equivalent knowledge.\n\nThe university may grant an exception to the basic eligibility requirement for an individual applicant if there are special reasons. (7 chap. 39 \u00a7 HF). For special eligibility requirements, see the study plan for the subject.\nWe are seeking candidates with:\nstrong knowledge of linear algebra, probability theory, and analysis\ngood programming skills\ninterest in method development within applied mathematics and statistics\ngood communication skills and sufficient knowledge of English in speech and writing\ncreativity, precision, and a structured approach to problem-solving\n\nDesirable\/Meriting Experience\nExperience in one or more of the following areas is meriting:\nBayesian statistics,\nmathematical modeling,\nstatistical machine learning.\n\nRegulations for PhD students can be found in the Higher Education Ordinance 5 chap \u00a7\u00a7 1-7 and in the university's rules and guidelines.\nApplication\nThe application should contain:\na personal letter (maximum 1 page) where you explain how you meet the qualifications, explain why you are applying for this position, and your estimated earliest start date;\na curriculum vitae (CV);\ndiplomas and transcripts with grades (translated into English or Swedish);\na thesis report (or draft thereof, and\/or other self-produced technical or scientific text), publications, and other relevant documents;\nreferences with contact information (name, email, and telephone number) and up to two letters of recommendation.\n\nAbout the Position\nThe position is time-limited, according to HF 5 chap \u00a7 7. Full-time employment. Start date: November 15, 2026, or by agreement. Location: Uppsala.\nInformation about the position is provided by: Assistant University Lecturer Sara Hamis, email: sara.hamis@it.uu.se.\nWelcome to submit your application no later than October 16, 2026, UFV-PA 2026\/2836.","language":"sv","is_translated":true,"title_original":"Doktorand i maskininl\u00e4rning","description_original":"Observera att detta \u00e4r en f\u00f6rkortad version av annonsen. F\u00f6r att se den fullst\u00e4ndiga annonsen v\u00e4nligen klicka p\u00e5 \u201dAns\u00f6k h\u00e4r\u201d eller se Uppsala universitets hemsida f\u00f6r jobbannonser: https:\/\/www.uu.se\/om-uu\/jobba-hos-oss\/lediga-jobb\n\u00c4r du intresserad av sannolikhetsteori, statistik och matematisk modellering? Vill du utveckla nya metoder f\u00f6r os\u00e4kerhetskvantifiering och till\u00e4mpa dessa metoder p\u00e5 storskaliga kliniska cancerdata? Vill du ha en arbetsgivare som satsar p\u00e5 ett h\u00e5llbart medarbetarskap och erbjuder trygga, f\u00f6rm\u00e5nliga arbetsvillkor? V\u00e4lkommen att s\u00f6ka anst\u00e4llning som doktorand p\u00e5 Institutionen f\u00f6r informationsteknologi vid Uppsala universitet.\nOm forskningsprogrammet DDLS\nDoktorandtj\u00e4nsten \u00e4r del av det nationella forskningsprogrammet DDLS.\nDatadriven livsvetenskap (Data-driven life science, DDLS) anv\u00e4nder data, ber\u00e4kningsmetoder och artificiell intelligens f\u00f6r att studera biologiska system och processer p\u00e5 alla niv\u00e5er \u2013 fr\u00e5n molekyl\u00e4ra strukturer och cellul\u00e4ra processer till m\u00e4nniskors h\u00e4lsa och globala ekosystem.\u00a0SciLifeLab\u00a0och\u00a0Wallenberg National Program for Data-Driven Life Science\u00a0(DDLS) syftar till att rekrytera och utbilda n\u00e4sta generation datadrivna livsvetenskapsforskare samt att skapa globalt ledande kompetens inom ber\u00e4knings- och datavetenskap i Sverige. Programmet finansieras med totalt 3,3 miljarder kronor \u00f6ver 12 \u00e5r fr\u00e5n\u00a0Knut och Alice Wallenbergs Stiftelse\u00a0(KAW).\n\u00c5r 2026 kommer DDLS forskarskola att ut\u00f6kas genom rekrytering av 25 akademiska och 7 industridoktorander. Under programmets g\u00e5ng kommer mer \u00e4n 260 doktorander och 200 postdoktorer att vara en del av forskarskolan. DDLS-programmet har fyra strategiska forskningsomr\u00e5den: cell- och molekyl\u00e4rbiologi, evolution och biologisk m\u00e5ngfald, precisionsmedicin och diagnostik samt epidemiologi och infektionsbiologi. F\u00f6r mer information, se:\u00a0https:\/\/www.scilifelab.se\/data-driven\/ddls-research-school\/\nLivsvetenskapens framtid \u00e4r datadriven. Vill du vara en del av den f\u00f6r\u00e4ndringen? D\u00e5 \u00e4r du v\u00e4lkommen att delta i detta unika program!\nVid\u00a0Uppsala universitet\u00a0utlyser vi nu en doktorandtj\u00e4nst inom DDLS med inriktning mot datadriven precisionsmedicin och diagnostik.\nDatadriven precisionsmedicin och diagnostik omfattar dataintegration, analys, visualisering och tolkning av data f\u00f6r patientstratifiering, uppt\u00e4ckt av biomark\u00f6rer f\u00f6r sjukdomsrisk, diagnostik, l\u00e4kemedelssvar och h\u00e4lsouppf\u00f6ljning. Forskningen inom precisionsmedicin f\u00f6rv\u00e4ntas anv\u00e4nda befintliga starka resurser i Sverige och internationellt, s\u00e5som molekyl\u00e4ra data (t.ex. omikdata), bilddata, elektroniska patientjournaler, longitudinella patient- och populationsregister samt biobanker.\nProjektbeskrivning\nDatadrivna matematiska och statistiska modeller anv\u00e4nds i allt st\u00f6rre utstr\u00e4ckning inom livsvetenskaplig forskning och h\u00e4lso- och sjukv\u00e5rd. Att kvantifiera os\u00e4kerheten i dessa modeller \u00e4r avg\u00f6rande f\u00f6r att f\u00f6rst\u00e5 deras tillf\u00f6rlitlighet och f\u00f6r att kunna fatta v\u00e4lgrundade beslut baserat p\u00e5 deras prediktioner. Detta projekt syftar till att utveckla nya metoder f\u00f6r os\u00e4kerhetskvantifiering i matematiska och statistiska modeller. Metoderna kommer att till\u00e4mpas p\u00e5 storskaliga kliniska cancerdata. En central till\u00e4mpning kommer att vara att kvantifiera os\u00e4kerheten i information som extraheras fr\u00e5n medicinska rapporter och att f\u00f6ra denna os\u00e4kerhet vidare till probabilistiska modeller som predicerar tid till h\u00e4ndelse.\nArbetsuppgifter\nDoktoranden ska fr\u00e4mst \u00e4gna sig \u00e5t den egna forskarutbildningen. \u00d6vrig tj\u00e4nstg\u00f6ring vid institutionen, som avser undervisning och administrativt arbete, kan ing\u00e5 inom ramen f\u00f6r anst\u00e4llningen (max 20%).\nKvalifikationskrav \nGrundl\u00e4ggande beh\u00f6righet till utbildning p\u00e5 forskarniv\u00e5 har den som:\navlagt examen p\u00e5 avancerad niv\u00e5 inom till\u00e4mpad matematik, till\u00e4mpad statistik, teknisk fysik, fysik, maskininl\u00e4rning, eller inom ett liknande omr\u00e5de, eller\nfullgjort minst 240 h\u00f6gskolepo\u00e4ng, varav minst 60 h\u00f6gskolepo\u00e4ng p\u00e5 avancerad niv\u00e5 inklusive ett sj\u00e4lvst\u00e4ndigt arbete om minst 15 h\u00f6gskolepo\u00e4ng, eller\np\u00e5 n\u00e5got annat s\u00e4tt inom eller utom landet f\u00f6rv\u00e4rvat i huvudsak motsvarande kunskaper.\n\nH\u00f6gskolan f\u00e5r f\u00f6r en enskild s\u00f6kande medge undantag fr\u00e5n kravet p\u00e5 grundl\u00e4ggande beh\u00f6righet, om det finns s\u00e4rskilda sk\u00e4l. (7 kap. 39 \u00a7 HF). F\u00f6r s\u00e4rskild beh\u00f6righet, se studieplanen f\u00f6r \u00e4mnet.\u00a0\nVi s\u00f6ker kandidater med:\nstarka kunskaper i linj\u00e4r algebra, sannolikhetsteori och analys\ngoda f\u00e4rdigheter i programmering\nintresse f\u00f6r metodutveckling inom applicerad matematik och statistik\ngod kommunikationsf\u00f6rm\u00e5ga och tillr\u00e4ckliga kunskaper i engelska i tal och skrift\nkreativitet, noggrannhet och ett strukturerat arbetss\u00e4tt i probleml\u00f6sning\n\n\u00d6nskv\u00e4rt\/meriterande i \u00f6vrigt\nErfarenhet inom ett eller flera av f\u00f6ljande omr\u00e5den \u00e4r meriterande:\nBayesiansk statistik,\nmatematisk modellering,\nstatistisk maskininl\u00e4rning.\n\nBest\u00e4mmelser f\u00f6r doktorander \u00e5terfinns i H\u00f6gskolef\u00f6rordningen 5 kap \u00a7\u00a7 1-7 samt i universitetets regler och riktlinjer.\nAns\u00f6kan\nAns\u00f6kan ska inneh\u00e5lla:\nett personligt brev (h\u00f6gst 1 sida) d\u00e4r f\u00f6rklarar hur du uppfyller kvalifikationskraven, motiverar varf\u00f6r du s\u00f6ker denna tj\u00e4nst, och ditt ber\u00e4knade tidigaste startdatum;\nen meritf\u00f6rteckning (CV);\nexamensbevis och registerutdrag med betyg (\u00f6versatt till engelska eller svenska);\nexamensrapport (eller utkast till s\u00e5dan, och\/eller annan egenproducerad teknisk eller vetenskaplig text), publikationer och andra relevanta dokument;\nreferenser med kontaktinformation (namn, e-post och telefonnummer) och upp till tv\u00e5 rekommendationsbrev.\n\nOm anst\u00e4llningen\u00a0\nAnst\u00e4llningen \u00e4r tidsbegr\u00e4nsad, enligt HF 5 kap \u00a7 7. Omfattningen \u00e4r heltid. Tilltr\u00e4de 15 november 2026 eller enligt \u00f6verenskommelse. Placeringsort: Uppsala.\nUpplysningar om anst\u00e4llningen l\u00e4mnas av: Bitr\u00e4dande universitetslektor Sara Hamis, e-mail: sara.hamis@it.uu.se.\u00a0\nV\u00e4lkommen med din ans\u00f6kan senast den 16 oktober 2026, UFV-PA 2026\/2836.","available_locales":["en"],"price":null,"currency":"SEK","status":"active","noindex":true,"location":{"address":"Regementsv\u00e4gen 10","full_address":null,"city":"Uppsala","country":"SE","latitude":59.839570068472,"longitude":17.646119822441},"metadata":{"region":"Uppsala l\u00e4n","duration":"6 m\u00e5nader eller l\u00e4ngre","employer":"Uppsala Universitet","postcode":"75237","positions":1,"profession":"Doktorand","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":4,"ai_views_count":5,"bot_views_count":0,"ai_vendor_counts":{"other":1,"openai":2,"anthropic":2},"visibility":"public","submission_source":null,"submission_ai_name":null,"has_owner_email":true,"can_contact_owner":true,"phone":null,"owner_email":"sara.hamis@it.uu.se","images":[],"published_at":"2026-09-23T12:58:40+00:00","expires_at":"2026-10-16T23:59:59+00:00","created_at":"2026-09-24T03:52:40+00:00","updated_at":"2026-09-27T03:19:30+00:00"}}