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KTH Royal Institute of Technology

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PhD and Postdoctoral Openings in Machine Learning, Multimodal Learning, and Digital Olfaction at KTH Royal Institute of Technology KTH Royal Institute of Technology in Sweden

Degree Level

PhD, Postdoc

Field of study

Computer Science

Funding

Multiple fully funded openings are advertised: research engineer, PhD, and postdoctoral researcher positions at KTH. The research engineer role is up to 6 months with monthly salary; the PhD position is a salaried doctoral appointment under KTH doctoral salary agreement; the postdoc is a time-limited research appointment up to 2 years with monthly salary. The post explicitly states the openings are fully funded.

Deadline

Expired

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Country

Sweden

University

KTH Royal Institute of Technology

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Keywords

Computer Science
Machine Learning
Chemistry
Signal Processing
Electrical Engineering
Deep Learning
Eeg
Neuropsychology
Biosignal Processing
Large Language Models

About this position

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.

Funding details

Multiple fully funded openings are advertised: research engineer, PhD, and postdoctoral researcher positions at KTH. The research engineer role is up to 6 months with monthly salary; the PhD position is a salaried doctoral appointment under KTH doctoral salary agreement; the postdoc is a time-limited research appointment up to 2 years with monthly salary. The post explicitly states the openings are fully funded.

What's required

PhD opening requires a master's degree or equivalent advanced-level qualification and English proficiency equivalent to English B/6. The postdoc requires a completed PhD by the appointment date, preferably within three years of the PhD at the application deadline. Strong backgrounds in ML/AI, signal processing, computational neuroscience, or related fields are preferred. For the postdoc, experience with deep learning architectures, multimodal representation learning, time-series modeling (EEG/video/sensor data), chemical/structural representations (graphs, SMILES, molecular embeddings), Python, and ML frameworks such as PyTorch, TensorFlow, or JAX is highly desirable. The research engineer role requires a completed degree at first or second cycle level or equivalent competence, plus relevant subject knowledge and the ability to work independently and collaboratively.

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