Humlab is a work unit and research infrastructure with around twenty employees at the Faculty of Arts and Humanities. Humlab’s mission is to initiate, inspire, and develop the interaction between the humanities, culture and information technology. Humlab’s premises are located in two buildings on campus: one in the Humanities building and another in the Social Science Building located below the University Library, where Humlab’s laboratory environment is also situated. In this creative and interdisciplinary environment, lectures, workshops and other events are offered to researchers, students, and the general public.

Job Description:   
The primary tasks involve working within the visualization infrastructure InfraVis, as well as other infrastructures at Humlab, alongside Humlabs general operations.

This includes:
• Node Coordinator (approx. 20% from 2025 onward) within the national infrastructure InfraVis. This role entails leading the work at Umeå University’s local InfraVis node (Humlab) and coordinating and co-organising activities with other nodes at other universities.
• InfraVis Application Expert (IAE) (60% during 2025, 55% during 2026 and estimated between 20–40% from 2027), with a focus on providing expert support and developing solutions for research projects that require expertise primarily in GIS and network analysis.
• Contributing to Humlab’s regular program activities, which may involve developing and conducting short courses, participating in various events and arrangements, supporting teachers and researchers at the Faculty of Arts and Humanities regarding GIS and/or network analysis.
• Working within Humlab’s other infrastructures (e.g. HumInfra).
• Work may also include teaching to a lesser extent, teaching planning and development, supervision, and supporting research project applications.

Tasks may change over time.

Qualifications required:
To be eligible for appointment as staff scientist, candidates must have:
• A PhD in a relevant field for data visualization, GIS, and network analysis, such as geographic information science, geography, geoinformatics, cartography or geosciences.
• Several years of theoretical and practical experience in working with GIS.
• Expertise in network analysis and associated tools.
• Strong collaboration and initiative skills.

Other desirable qualifications:
• Experience of coordinating group work, which is valuable for the Node Coordinator role within InfraVis.
• Experience working in digital humanities, aiding the understanding of user groups’ needs and research questions.
• Practical experience with GIS tools ArcGIS or QGIS.
• Experience working with GIS-related research data, including data collection and processing.
• Ability to develop “ready-to-use” solutions and user interfaces within GIS (e.g., ArcGIS Online) for visualizing research data.

Application:
The application shall include:
1. A cover letter (1–2 pages) with motivations to your interest in the position, detailing your qualifications, and describing their relevance to the job.

2. A CV (Curriculum Vitae).

3. Relevant degrees and certifications supporting the information stated in the CV.

Applications must be submitted via e-recruiting system Varbi no later than September 12, 2025. Documents must be written in Swedish or English. A probationary period may apply.

Other information:
For more details about the position, contact:
Karin Danielsson, Director, Humlab, Phone: +46 (0)90-786 65 86, E-mail: karin.danielsson@umu.se
Questions regarding the recruitment process are answered by:
Anneli Taflin, HR-coordinator, Humlab, Phone: + 46 (0)90-786 89 31, E-mail: anneli.taflin@umu.se

For more information, visit:
• Humlab: https://www.umu.se/humlab  
• InfraVis: https://www.infravis.se

Welcome with your application!

Department of computing science 

The Department of Computer Science has experienced significant growth in recent years. The department is involved in several national and international research projects. Creating an inclusive research environment where employees are highly engaged is a key factor in our sustainable development. Our department consists of a diverse group of people from various nationalities, backgrounds, and fields.
Read more at https://www.umu.se/institutionen-for-datavetenskap/ 

Project description  

The purpose of the research project is to identify factors that may undermine the trustworthiness of data and models used in human-robot interaction and further investigates common and specific trustworthiness issues related to fairness and safety in human-robot interaction applications.  An AI trustworthiness model will be developed and validated ensuring that both data and models of human interaction are robust, especially in the selected industry use cases.

This staff scientist position is linked to the research group Deep Data Mining in the department of Computing Science, which focuses on fusing data science and artificial intelligence and developing AI trustworthiness (e.g., fairness, privacy, safety) models.   The project is part of the EU project XSCAVE (https://www.xscave.eu/) whose ambition lies on large scale deployment of autonomous heavy mobile machines in earthmoving, forestry and urban logistics industries. The XSCAVE consortium involves eleven partners from all over Europe.

To meet these needs, we are now looking for a staff scientist. The position is temporary for 12 months on full time and is expected to start in February 2026 or according to agreement.

The project offers opportunities for:

• Participating in pioneering research and innovation initiatives, gaining interdisciplinary knowledge.
• Internal and international collaborations with academic research groups and industrial companies in the field of AI robotics, large language modelling, simulation, mobile robotics, and off-road heavy equipment.

Duties and responsibilities   

As a staff scientist with us, your main duties will include:

• Investigate elements that may undermine the trustworthiness of data and models used in human-robot interaction.
• Develop and validate an AI trustworthiness model that addresses bias and ensures safety to promote transparency.
• Collaborate with partners to enhance the trustworthiness model by mitigating identified risks associated with large language models (LLMs).
• Research dissemination (e.g., peer review scientific publications, presentations).

Qualifications 

You need:

• A PhD degree in computer science, mathematics, or engineering physics, preferably with a focus on data analysis, AI trustworthiness, human robotics development.
• Hands-on experience in the field of data science.
• Communication skills in English

Other desirable merits:

• Practical experience in AI trustworthiness-related topics (e.g., fairness, privacy or explainable AI or safety).
• Experience in machine learning, causal inference, image processing, human-robot interaction, or large language models.
• Experience in analyzing multimodal data (e.g., text, sensor, images etc.).

Personal characteristics:

• Ability to work independently, with effective problem-solving skills and a collaborative mindset.
• Ability to communicate and document your work.
• Ability to disseminate research achievements through peer review publications.

Application 

Your application should include:

• Cover letter in which you provide a brief description of your research interests and a statement describing why you are interested in the position (no more than 2 A4 pages).
• CV with publication list.
• Verified copy of doctoral degree certificate and other relevant degree certificates.
• Copy of doctoral thesis and up to five relevant articles,
• Other documents that the applicant wishes to claim.
• Contact information to two persons willing to act as references.

The application should be written in English or Swedish.

Contact:  For further information, please contact associate professor Lili Jiang (lili.jiang@umu.se).

Apply via our e-recruitment system Varbi no later than 2025-09-10. Start date 2026-02-01 or as agreed.

High-Performance Computing Center North (HPC2N), Umeå University and NAISS are seeking two or more candidates for the position of Staff Scientist, working as application experts within the newly established, EU-funded Swedish AI Factory. Closing date: September 5, 2025.

NAISS, the National Academic Infrastructure for Supercomputing in Sweden, provides academic users with high-performance computing resources, storage capacity, and data services. NAISS is hosted by Linköping University and comprises 12 partner universities across Sweden. Umeå University is one of them.

This opening is in connection with the EuroHPC-funded Swedish AI Factory, a collaboration between NAISS and RISE AB. The project will bring together more than 40 experts in AI and ML, as well as technical staff, to support both academic and industrial users across the EuroHPC member states towards advancing AI solutions, education, innovation, and competence development.
For more information: https://eurohpc-ju.europa.eu/ai-factories_en  

Job Description

As a Staff Scientist, you will work in the capacity of an application expert, supporting researchers in carrying out concrete AI projects. Your role is to educate yourself with the target application to then provide help and guide researchers in aspects related to AI. These include tasks such as advising on methods and systems, assessing quality and properties of data, assisting with resource allocation proposals, machine learning workflows, dataset curation, organization, and sharing, data visualization, as well as model validation, tuning, testing, and interpretation. The role also involves organizing training and joint activities in collaboration with other infrastructures in Sweden and across the EU.

Responsibilities

• Provide expert-level support and guidance to users applying AI/ML techniques in their work
• Assist users in selecting appropriate models, tools, and pipelines
• Develop and deliver training materials, tutorials, and workshops tailored to different audiences
• Stay current with the latest developments in AI/ML and assess their applicability.

Qualifications

To be appointed, the applicant is required to have completed a doctoral degree or a foreign degree deemed equivalent to a doctoral degree. This requirement must be fulfilled no later than at the time of the appointment decision.

Requirements

• A doctoral degree related to Data Science, involving applied work in machine learning
• Experience with common ML frameworks (e.g., Tensorflow, PyTorch)
• Expert knowledge of Python or C/C++
• Experience in large-scale computing and/or curating, handling, evaluating large-scale datasets
• Excellent communication skills in oral and written English
• Ability to convincingly convey the importance and impact of a complex scientific project to a broad range of stakeholders.

Merits

• Experience in developing custom AI models
• Experience in writing proposals for compute time or similar research resources
• Experience in collaboration with industry or public sector organizations
• Knowledge of R, Matlab, Julia.

High demands are placed on being able to plan, organize, document and follow up one’s work independently, but also on cooperation and on the ability to communicate with colleagues and users.

Terms of employment

This is a full-time, permanent position, and a probationary period may be applied. Start date as per agreement.

Information

More information about the position can be given by HPC2N director Paolo Bientinesi, tel +46 720 856 180, pauldj@cs.umu.se

Application

Your application must be written in Swedish or English and should contain:

• A cover letter, max 2 A4 pages, that motivates your interest in this position and that explains why you are the person to be hired.
• A curriculum vitae
• Electronic link to doctoral dissertation and all relevant publications.
• Copies of degree certificates, including documentation of completed academic courses and obtained grades.
• Contact information for at least two reference persons.
• Description of and link to other relevant experiences or competences, including software projects.

Should the submitted material be in a language different from Swedish or English, an English translation must be included too.

HPC2N

High Performance Computing Center North (HPC2N) is one of Sweden’s leading supercomputing centers, and member of NAISS (National Academic Infrastructure for Supercomputing in Sweden). HPC2N is hosted by Umeå University and has a partnership with the Institute of Space Physics, Luleå University, Mid Sweden University, the Swedish University of Agricultural Sciences, and Umeå University.

HPC2N is operating high-performance parallel computer systems and networks, large-scale disk and tape storage systems. All levels of user support are offered, to make sure researchers can make use of our resources in the best possible way.

For more information about HPC2N: http://www.hpc2n.umu.se