Valentas Gružauskas
2 months ago
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Postdoctoral Fellowship in Uncertainty-Aware Foundation Models for Earth Observation Vilnius University in Lithuania
Degree Level
Postdoc
Field of study
Computer Science
Funding
Available
Deadline
Sep 7, 2026
Country
Lithuania
University
Vilnius University

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About this position
Vilnius University is offering a Postdoctoral Fellowship in Uncertainty-Aware Foundation Models for Earth Observation at the Institute of Computer Science, Faculty of Mathematics and Informatics, within the AI Methods Lab in Vilnius, Lithuania.
The project focuses on research into uncertainty-aware foundation models and vision-language models for Earth observation, multi-task environmental monitoring, and trustworthy geospatial AI. The successful candidate will work on methods for making large-scale environmental models not only accurate, but also reliable and well-calibrated. Research directions include deep ensembles, Bayesian and evidential approaches, conformal prediction, and post-hoc calibration; adaptation and benchmarking of Earth observation foundation and vision-language models; and multi-task applications such as land-cover mapping, semantic segmentation, classification, change detection, and climate-related analyses.
The fellowship is hosted in a multidisciplinary and collaborative environment with international partners. The postdoctoral researcher will work with heterogeneous remote sensing and in-situ data, including Sentinel, Landsat, and MODIS archives, along with environmental variables, geospatial metadata, and sensor/IoT streams. The project also emphasizes robustness, transferability, and uncertainty calibration across tasks, sensors, regions, and changing acquisition conditions.
Supervision is planned by Assoc. Prof. Dr. Valentas Gružauskas, with collaboration possibilities involving Assoc. Prof. Linas Petkevičius. The research group is based at the AI Methods Lab and is connected to work on remote sensing and new foundation vision-language models. The broader context includes reproducible experimentation, HPC-based PyTorch pipelines, open-source release, and scientific publication in high-impact venues.
This is a full-time temporary postdoc position for 12 months. The monthly salary is €3,634.00 gross before tax. Candidates must be able to work in Lithuania at the premises of Vilnius University; remote-only candidates will not be considered.
Eligibility requirements include a doctoral degree, preferably awarded by a foreign institution or by a Lithuanian science institution other than Vilnius University, and the PhD must normally have been awarded no more than five years ago (with formal extensions possible for documented parental leave). Applicants should have strong expertise in deep learning, computer vision, remote sensing, or multimodal AI, plus experience with Python, PyTorch, satellite imagery or geospatial data, and English at B2 level or higher. Publications in machine learning, AI, or computer vision are expected. Experience in mentoring or grant writing is an advantage.
Applications must be submitted by email with the official Vilnius University application form and mandatory attachments: CV, list of publications (up to 10 key items), and a copy of the PhD diploma. The email subject line must state exactly postdoctoral fellowship.
Application deadline: 7 September 2026, 23:59 (Europe/Vilnius).
Funding details
Available
What's required
Applicants must hold a PhD or equivalent degree. Eligible candidates must have a doctoral degree awarded by a foreign institution (preferred) or by a Lithuanian science institution other than Vilnius University, and no more than 5 years must have elapsed since the PhD award date (with possible extension for documented maternity, paternity, or parental leave). Strong background in deep learning, computer vision or remote sensing is expected, ideally including semantic segmentation or multi-task learning. Experience with vision-language models and multimodal AI systems, Python, PyTorch, and modern ML frameworks is required, as is experience with satellite imagery or geospatial data. Candidates should have good English at B2 level or higher, strong written and oral communication skills, familiarity with uncertainty quantification methods such as deep ensembles, Bayesian approximations, conformal prediction or calibration, publications in machine learning/AI/computer vision or related areas, strong analytical and problem-solving skills, ability to design and implement AI research prototypes, and the motivation to work in interdisciplinary international teams. Experience in academic mentoring and drafting technical grant proposals is considered an advantage. Strong preference is given to candidates who obtained their PhD from prestigious international research institutions outside Lithuania.
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