Danica Kragic Jensfelt

The KTH Royal Institute of Technology invites applications for a doctoral student position in Robot Learning for Manipulation. This PhD opportunity is situated within the third-cycle subject of Computer Science and focuses on advancing robot learning for manipulation tasks, particularly leveraging Vision-Language-Action (VLA) models. The research aims to explore tabletop manipulation and extend to complex mobile manipulation scenarios, emphasizing the integration of whole-body motion to enhance perception and control. Supervision will be provided by Professor Danica Kragic Jensfelt, a leading expert in robotics and machine learning. The project is ideal for candidates with a strong background in robotics and machine learning, and who have demonstrated experience in at least two of the following areas: deep learning, reinforcement learning, robot perception, navigation, or manipulation. The research environment at KTH is dynamic and creative, offering excellent working conditions, employee benefits, and opportunities for professional growth. Admission requirements include a second cycle degree (such as a master's degree) or equivalent, or completion of at least 240 higher education credits (with at least 60 at second-cycle level). English proficiency equivalent to English B/6 is mandatory. Selection criteria emphasize personal skills such as goal orientation, perseverance, independence, collaboration, professionalism, and analytical ability. Only those admitted to postgraduate education may be employed as a doctoral student, with employment lasting up to four years full-time. The position offers a monthly salary according to KTH’s doctoral student salary agreement and includes employee benefits. Applicants must submit a CV, application letter (maximum 2 pages), certified copies of diplomas and grades, proof of language proficiency, and representative publications or technical reports. Documents not in English or Swedish must be translated and certified. Applications are processed through KTH's recruitment system and must be received by the deadline. Security clearance may be required for certain positions. KTH Royal Institute of Technology is a leading international technical university located in Stockholm, Sweden. The institution is committed to equality, diversity, and sustainability, providing a supportive environment for doctoral students. Join KTH to contribute to cutting-edge research in robot learning and manipulation, and to shape the future of technology and society.

KTH Royal Institute of Technology in Stockholm, Sweden, invites applications for postdoctoral positions in robot learning for manipulation. The successful candidates will join a leading international technical university and work on cutting-edge research exploring Vision–Language–Action (VLA) models for both tabletop and mobile robotic manipulation. The research will focus on leveraging whole-body, humanoid-style motion to enhance perception and control, enabling robots to perform complex, coordinated tasks in dynamic environments. Applicants should have a strong background in robotics and machine learning, with demonstrated experience in at least two of the following areas: deep learning, reinforcement learning, imitation learning, robot perception, navigation, and manipulation. Experience with whole-body control, humanoid or multi-degree-of-freedom (DOF) platforms, and learning-based manipulation in simulation and/or real systems is highly valued. The position requires a doctoral degree (or equivalent foreign degree) in a relevant field, strong programming skills, an excellent research and publication record, and advanced analytical and problem-solving abilities. Proficiency in English, both written and spoken, is essential. Preferred qualifications include a doctoral degree obtained within the last three years, pedagogical skills, awareness of diversity and equal opportunity issues (with a focus on gender equality), independence, and strong collaboration skills. The appointment is for up to two years, full-time, and offers a monthly salary with attractive benefits and good working conditions. KTH is committed to equality, diversity, and providing a creative and dynamic research environment. To apply, candidates must submit a complete application through KTH's recruitment system, including a CV, diplomas and grades (with translations if necessary), and a brief statement of research interests and goals (maximum two pages). The application deadline is January 15, 2026. For further information, contact Professor Danica Kragic Jensfelt at [email protected]. For more details and to apply, visit the official application link.

Two fully funded PhD positions are available in the group of Professor Danica Kragic Jensfelt at the Department of Robotics, Perception, and Learning, KTH Royal Institute of Technology, Stockholm, Sweden. The research focuses on robot learning for manipulation, with an emphasis on leveraging recent advances in Vision-Language-Action (VLA) models for tabletop manipulation tasks. The projects aim to enhance perception and control by utilizing whole-body motion to solve complex mobile manipulation challenges. Applicants should have a strong background in robotics and machine learning, with demonstrated experience in at least two of the following areas: deep learning, reinforcement learning, robot perception, navigation, or manipulation. The positions are part of the Computer Science doctoral program at KTH, a leading international technical university known for its dynamic research environment and commitment to sustainability, equality, and innovation. Eligibility requires a second cycle degree (such as a master's) or equivalent, with at least 240 higher education credits (including 60 at the second-cycle level), and proficiency in English equivalent to English B/6. Selection will consider academic qualifications, relevant experience, motivation, and personal skills such as independence, collaboration, and analytical ability. The positions are fully funded, offering a monthly salary according to KTH's doctoral student salary agreement, full-time employment, and a range of employee benefits. The total duration is up to four years, with annual renewals possible. The application deadline is March 5, 2025. To apply, candidates must submit a complete application via the KTH Application Portal, including a CV, application letter, diplomas, transcripts, proof of English proficiency, and representative publications. For more information, visit the official job posting or contact Professor Danica Kragic Jensfelt at [email protected].

KTH Royal Institute of Technology in Stockholm, Sweden, invites applications for a postdoctoral position in Robot Learning for Manipulation. The successful candidate will join a dynamic research environment focused on advancing state-of-the-art Vision–Language–Action (VLA) models for both tabletop and mobile robotic manipulation. The research aims to leverage whole-body, humanoid-style motion to enhance perception and control, enabling robots to perform complex, coordinated tasks in dynamic environments. The position is ideal for candidates with a strong background in robotics and machine learning, and demonstrated experience in at least two of the following areas: deep learning, reinforcement learning, imitation learning, robot perception, navigation, and manipulation. Experience with whole-body control, humanoid or multi-DOF platforms, and learning-based manipulation in simulation and/or real systems is highly valued. Applicants must hold a doctoral degree or an equivalent foreign degree in a relevant field, to be completed no later than the employment decision. Essential qualifications include research expertise in machine learning/robotics, strong programming skills, an outstanding research and publication record, and excellent analytical and problem-solving abilities. Proficiency in English (written and oral) is required. Preferred qualifications include a doctoral degree obtained within the last three years, pedagogical ability, awareness of diversity and equal opportunity issues, independence, and strong collaboration skills. The appointment is full-time, temporary (up to two years), and offers a monthly salary. KTH provides a creative and dynamic environment with excellent working conditions and attractive benefits. The university is committed to equality, diversity, and equal opportunities as core values. To apply, submit your application through the KTH recruitment system. Required documents include a CV, copies of diplomas and grades (with translations if not in English or Swedish), and a brief research statement (maximum two pages) outlining your academic interests and how they relate to your previous studies and future goals. Applications must be received by midnight CET on April 14, 2026. For further information, contact Professor Danica Kragic Jensfelt at [email protected]. The position reference number is PA-2026-1035.

The KTH Royal Institute of Technology in Stockholm, Sweden, invites applications for postdoctoral positions in Machine Learning for Olfaction. This opportunity is part of the EU project “Digitising Smell: From Natural Statistics of Olfactory Perceptual Space to Digital Transmission of Odors,” which aims to digitalize the sense of smell and advance our understanding of olfaction in humans. The project also seeks to build AI models capable of simulating olfactory experiences, bridging the gap between neuroscience, chemistry, and machine learning. As a postdoctoral researcher, you will focus on processing and developing representation models for diverse data sources, including time-series data (EEG, video, mass spectrometry) and chemical data (molecular graphs, SMILES strings) related to odorant stimuli. The research environment is highly interdisciplinary, offering collaboration across machine learning, neuroscience, and chemistry. You will work with deep learning architectures such as Transformers, diffusion models, and graph neural networks, applying them to multimodal and high-dimensional data. Expertise in time-series modeling, chemical/structural data representation, signal processing, and statistical modeling is essential. Applicants must hold a doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline. Strong programming skills in Python and relevant machine learning frameworks (PyTorch, TensorFlow, JAX) are required. The ideal candidate will demonstrate proven research experience with deep learning, multimodal representation learning, and integration of heterogeneous data sources. Excellent communication and collaborative skills, motivation, and dedication to research are highly valued. Teaching and supervision experience is considered an advantage. Awareness of diversity and equal opportunity issues, with a specific focus on gender equality, is expected. KTH Royal Institute of Technology is a leading international technical university, committed to advancing education, research, and innovation for a sustainable society. The institution offers a creative and dynamic environment, attractive benefits, and good working conditions. The postdoctoral position is full-time, temporary (up to two years), and comes with a monthly salary. The position may be classified as security-sensitive, requiring a security clearance in accordance with Swedish law. To apply, log into KTH's recruitment system and submit your application by May 17, 2026. Your application should include a CV, diplomas and grades, translations if necessary, and a brief account of your research motivation and academic interests. For further information, contact Professor Danica Kragic Jensfelt at [email protected]. This is an excellent opportunity for early-career researchers with a strong background in machine learning, neuroscience, and chemistry to contribute to cutting-edge research in olfactory digitization and AI modeling. Join KTH and help shape the future of olfactory science and technology.

KTH Royal Institute of Technology is advertising multiple fully funded openings in an interdisciplinary project on digital olfaction —building AI systems that can model and simulate human smell perception. The post highlights three opportunities: a Research Engineer role, a PhD position , and a Postdoctoral researcher position. The research spans machine learning , multimodal learning , representation learning , biosignal processing (including EEG and other time-series data), large language and multimodal models , computational olfaction , and AI for perception research. The project is described as an international and interdisciplinary effort connecting machine learning , neuroscience , chemistry , and perception research . The postdoc description adds work on heterogeneous data sources such as EEG, video, mass spectrometry, text, images, and chemical representations like molecular graphs and SMILES strings. Eligibility highlights: the PhD call requires an advanced degree and English proficiency; the postdoc requires a PhD by the appointment date, with preference for recent graduates and candidates with strong deep learning, multimodal modeling, signal processing, and programming skills. The research engineer role asks for a completed degree at first or second cycle level or equivalent competence, plus relevant subject knowledge and the ability to work independently and collaboratively. Funding: the post states the openings are fully funded. The research engineer is a temporary appointment of up to 6 months, the PhD is a salaried doctoral position, and the postdoc is a time-limited research appointment of up to 2 years. Application: apply via KTH's recruitment system using the relevant portal for each role. The post provides separate links for the Research Engineer, PhD, and Postdoctoral researcher openings. Deadlines shown in the linked KTH postings are in June 2026. Institution: KTH Royal Institute of Technology, Stockholm, Sweden.

KTH Royal Institute of Technology is advertising multiple openings in machine learning , computational olfaction , multimodal sensing , and digital smell . The project aims to teach machines to understand and model human smell perception, combining representation learning, biosignal processing, EEG, time-series data, large language and multimodal models, and chemical/structural representations. Openings mentioned in the post include a PhD position , a postdoctoral researcher position, and a research engineer role. The research spans an international and interdisciplinary effort across machine learning, neuroscience, chemistry, and perception research. The KTH job pages indicate that the PhD project is linked to the EU project Digitising Smell: From Natural Statistics of Olfactory Perceptual Space to Digital Transmission of Odors , with one doctoral track focused on EEG/time-series/signal processing and another on computer vision, ML, and video processing. Research areas and keywords: machine learning, deep learning, multimodal learning, representation learning, computational neuroscience, signal processing, EEG, video, mass spectrometry, text, images, molecular graphs, SMILES, and computational olfaction. Eligibility highlights: the PhD role requires advanced-level academic eligibility and English proficiency equivalent to English B/6; the postdoc requires a completed PhD, with preference for recent graduates; the research engineer role requires a completed bachelor’s or master’s degree or equivalent competence. Strong programming and ML experience are emphasized, especially Python and frameworks such as PyTorch, TensorFlow, or JAX for the postdoc. Funding: the post explicitly says the openings are fully funded. The research engineer appointment is up to 6 months, the postdoc is up to 2 years, and the PhD is a salaried doctoral employment under KTH terms. Application: apply via KTH’s recruitment system using the relevant job link for each role. Prepare CV, degree certificates, transcripts, translations if needed, and a motivation letter; the PhD application also asks for representative publications or technical reports. Deadlines shown in the linked KTH postings are 2026-06-17 for the PhD, 2026-06-26 for the research engineer, and 2026-06-27 for the postdoc.

This postdoctoral position at KTH Royal Institute of Technology offers an exciting opportunity to join the EU project “Digitising Smell: From Natural Statistics of Olfactory Perceptual Space to Digital Transmission of Odors.” The project aims to digitalize the sense of smell, advancing our understanding of olfaction in humans and enabling the development of AI models that simulate olfactory experiences. As a postdoctoral researcher, you will focus on processing and developing representation models for diverse data sources, including time-series data (EEG, video, mass spectrometry), text, images, and chemical data (molecular graphs, SMILES strings) related to odorant stimuli. The research environment is highly interdisciplinary, bridging machine learning, neuroscience, and chemistry. You will work with deep learning architectures such as Transformers, diffusion models, and graph neural networks, applying them to multimodal and high-dimensional data. The project emphasizes multimodal representation learning and integration of heterogeneous data sources, requiring expertise in signal processing, statistical modeling, and advanced programming skills in Python and ML frameworks (PyTorch, TensorFlow, JAX). KTH Royal Institute of Technology is a leading international technical university located in Stockholm, Sweden. The institution is committed to education, research, and innovation, with a strong focus on sustainability, equality, diversity, and equal opportunities. The postdoctoral appointment is full-time and temporary, lasting up to two years, and offers a monthly salary with attractive benefits and good working conditions. Applicants must hold a doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline. Required qualifications include proven research experience with deep learning architectures applied to multimodal data, expertise in time-series modeling and chemical/structural data representation, familiarity with multimodal representation learning, signal processing, and statistical modeling of high-dimensional data, and strong programming skills. The ability to work collaboratively in interdisciplinary teams and excellent communication skills are essential. Teaching and supervision experience is an advantage. Applicants must submit diplomas and grades, with translations into English or Swedish if necessary. To apply, log into KTH's recruitment system and submit your application online. Include your CV, diplomas and grades (with translations if needed), and a brief account of your research motivation and academic interests. Ensure your complete application is received by midnight CET on the deadline date, 2026-06-27. For further information, contact Professor Danica Kragic Jensfelt at [email protected]. This position is a unique opportunity to contribute to cutting-edge research in olfactory modeling and machine learning, within a creative and dynamic academic environment at KTH.