GIS Software Developer

About the position ​ A three-year position as Postdoctoral Research Fellow in machine learning and artificial intelligence in epidemiology is available at the Department of Public Health and Interdisciplinary Health Science, Institute of Health and Society, Faculty of Medicine, University of Oslo. The position is linked to the project LINDA-FAMILIA – Implementation of an Integrated Digital Health System for Infectious Diseases in Maternal and Child Health in East Africa, a Horizon Europe/Global Health EDCTP3 project.  The postdoctoral fellow will contribute to a work package on clinical research co-led by the University of Oslo and the Uganda National Institute of Public Health. Up to 10% of the position will be devoted to career-promoting work, primarily teaching and supervision in machine learning and artificial intelligence for master students in epidemiology. About the project: ​ LINDA-FAMILIA will do research within digital eRegistries for reproductive, maternal, newborn and child health services in four regions in East Africa: Addis Ababa Region, Ethiopia; Eastern Province, Rwanda; Kilimanjaro Region, Tanzania; and Lango sub-Region, Uganda. The eRegistries are deployed to replace paper-based health information systems and support clinical care, disease surveillance and research through harmonized longitudinal individual-level data across the four countries. The systems include clinical decision support, referral coordination, targeted client communication, data management and interoperability. The project will demonstrate the scientific value of these routinely collected real-world eRegistry data for multi-country clinical and epidemiological research on poverty-related infectious diseases in maternal, perinatal, neonatal and child health. More about the position ​ The postdoctoral fellow will work at the interface of epidemiology, causal inference, prediction modelling, responsible AI, digital health and global maternal and child health. The work will include development and application of machine learning and AI methods to large-scale, longitudinal, routinely collected eRegistry data. The successful candidate will collaborate with researchers, PhD candidates, postdoctoral fellows, public health institutions and Ministries of Health in Ethiopia, Rwanda, Tanzania and Uganda, as well as partners in Europe. Some international travel for project meetings, workshops and collaboration with country teams should be expected. A career plan shall be developed for the Postdoctoral Fellow, specifying the competencies the Postdoctoral Fellow should acquire. UiO is responsible for following up on the career plan and ensuring that the Postdoctoral Fellow has access to career guidance throughout the postdoctoral term. Up to 10% of the position will be devoted to career-promoting work, primarily teaching and supervision in machine learning and artificial intelligence for master students in epidemiology. The duration of appointment is 3 years.  Your areas of responsibility will be ​ The successful candidate will: • Develop and apply machine learning and AI methods for epidemiological research using longitudinal eRegistry data. • Contribute to comparative epidemiological studies across countries and data systems. • Apply causal inference and targeted learning methods, including TMLE and Super Learner approaches where relevant. • Contribute to the development and validation of risk prediction models for severe maternal, perinatal, neonatal and child outcomes     related to poverty-related infectious diseases. • Contribute to geospatial epidemiology analyses using GIS-linked eRegistry data. • Develop reproducible R-based analysis pipelines, including support for DataSHIELD or other privacy-preserving/distributed analyses. • Contribute to data harmonization, data quality assessment, missing data strategies, data anonymization and data sharing procedures. • Contribute to protocols, statistical analysis plans and reporting for the registry-based cluster randomized trial of SMS and automated voice messaging reminders. • Collaborate with and support researchers in the partner countries, including training and capacity-building activities. • Publish results in peer-reviewed journals and present findings at international conferences and project meetings. • Contribute to teaching and supervision in machine learning and AI for master students. Qualifications ​ You must have​: • A degree equivalent to a Norwegian doctoral degree in epidemiology, biostatistics, statistics, machine learning, artificial intelligence, computer science, health data science, public health, medicine with strong quantitative methods, or a closely related field. • The doctoral dissertation must be submitted for evaluation by the application deadline. Appointment is dependent on the public defense of the doctoral thesis being approved before the start of employment. • Documented competence in statistical modelling, machine learning, artificial intelligence, causal inference, prediction modelling or related quantitative methods. • Experience with analysis of large, complex health data, such as longitudinal data, registry data, electronic health records, cohort data or trial data. • Strong programming skills in R, Python or equivalent scientific computing languages. Strong R skills are particularly relevant for this project. • Excellent written and oral communication skills in English.  Desired qualifications:​ Experience with one or more of the following will be considered an advantage: • Maternal, perinatal, neonatal or child health epidemiology. • Infectious disease epidemiology, poverty-related diseases or global health research in low- and middle-income countries. • Digital health, DHIS2, eRegistries, electronic health records or routine health information systems. • Targeted learning, TMLE, Super Learner, ensemble methods, causal machine learning or related methods. • Geospatial epidemiology and GIS methods. • DataSHIELD, federated learning or distributed multi-country data analysis. • Registry-based trials, cluster randomized trials or pragmatic trials. • Responsible AI, model validation, calibration, interpretability, bias assessment or fairness in health research. • Teaching or supervision in epidemiology, machine learning, AI, biostatistics or health data science. • Norwegian or another Scandinavian language is an advantage, but not a requirement. Personal qualities ​ We are looking for a candidate who:​ • Is motivated to develop an independent research profile in machine learning and AI for epidemiology. • Can work independently and systematically. • Has strong analytical and problem-solving skills. • Enjoys interdisciplinary and international collaboration. • Communicates well with researchers, clinicians, statisticians, software developers and public health partners. • Contributes to a collegial and inclusive working environment. Personal suitability will be emphasized. We need different perspectives in our work ​ UiO is an open and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no. We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds, and perspectives. We are looking for great colleagues—could you be the next one? We will do our best to accommodate your needs. Relevant adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures. If you have an immigrant background, a disability, or CV gaps, we encourage you to indicate this in the job application portal. We always invite at least one qualified candidate from each group for an interview. In this context, disability is defined as an applicant who identifies as having a disability that requires workplace or employment-related accommodations. For more details about the requirements, please refer to the Employer portal (Norwegian). The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports. More information about gender equality initiatives at UiO can be found here. We hope you will apply for the position with us.  We offer ​ •  A three-year postdoctoral position in an international and interdisciplinary research project. • Opportunity to develop an independent research profile in machine learning, AI and epidemiology. • Collaboration with research and public health partners in Norway, Ethiopia, Rwanda, Tanzania, Uganda and Europe. • Access to a large international project working with real-world maternal and child health data. • Career development support through the Faculty of Medicine’s postdoctoral program and an individual Career Development Plan. • Committed colleagues in a good working environment.  • Good welfare schemes. • Opportunity of up to 1.5 hours a week of exercise during working hours. • A workplace with good development and career opportunities.  • Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes. • Salary in position as Postdoctoral Fellow, position code 1352 in                                                                salary range NOK from 610 000 to 720 000,​ depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund. • Oslo’s family-friendly environment with rich opportunities for culture and outdoor activities.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. Read more about the benefits of working in the public sector at Employer Portal. Application​ Your application should include: • Application letter. • CV. • A complete list of publications. • Project description. • Transcripts and certificates. • Contact information for 2-3 references. Application with attachments must be submitted via our recruitment system Jobbnorge, click "Apply for the position". When applying for the position, we ask you to retrieve your education results from Vitnemålsportalen.no. 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. General information​ The best qualified candidates will invited for interviews.  Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 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. Please refer to Regulations for the Act on universities and colleges chapter 3 (Norwegian) and Guidelines concerning appointment to recruitment positions at UiO.  The University of Oslo has a transfer agreement with all employees that is intended to secure the rights to all research results etc.

Everything happens somewhere — which is why spatial analytics is fundamental to companies trying to understand the "where" and the "why" of their business. CARTO is the world's leading cloud-native spatial analysis platform, trusted by data scientists, analysts, and developers from global brands like IKEA, Coca-Cola, T-Mobile, Swiss Re, and AXA to run scalable spatial analysis directly on their cloud data warehouses and lakehouses. Built by a diverse team of over 150 people across the US, APAC, and Europe (backed by Insight Partners, Accel Partners, Salesforce Ventures, and Earlybird Ventures), CARTO is fundamentally changing how location data is analyzed — making it an integrated, accessible, AI-native part of modern data infrastructure. THE ROLE Spatial analytics is moving out of the GIS silo. It's moving into the warehouse, then into the lakehouse, then into Iceberg and open formats, and increasingly into agentic workflows where the consumer is no longer always a human. We're looking for an engineer who has been part of building that shift, to come help us lead where it goes next at CARTO. This role sits across CARTO's Analytics Toolbox and Workflows — the two surfaces through which our spatial analytics runs on partner engines (BigQuery, Snowflake, Redshift, Databricks, Postgres, Oracle) and, increasingly, on open formats consumed by external agents and applications. You'll define how the Toolbox framework evolves, how analytics capabilities are deployed across heterogeneous engines, and how CARTO plugs into the cloud-native geospatial stack — GeoParquet, STAC, Arrow, Iceberg, RaQuet, and what comes next. We don't think of this as a feature-shipping role. We think of it as a vision-and-execution role: someone who can write the strategy doc and own the PR that proves it works. WHERE YOU'D SIT You'd work alongside the Workflows team (backend, frontend, data engineering, QA — six people today, growing) and the broader Spatial Analytics group, with significant scope to shape the technical direction of both. This is a remote-first role open to candidates based anywhere in Spain. Offices in Madrid and Seville are available if you want them, not required.