Research Scientist
ATS Sweden HR AB
📍 Stockholm
⏰ Heltid
📋 Vanlig anställning
🗓 Ansök senast 11 maj 2026
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Research Scientist
In the short to medium term, this role will primarily focus on advancing the development and optimisation of state-of-the-art language decoding models. The successful candidate will play a key role in designing, training, and evaluating models that leverage both classical fMRI datasets acquired by Karavela, as well as external datasets, and progressively incorporate raw k-space data as it becomes available through Karavela’s data collection efforts.
This position offers a unique opportunity to work at the intersection of neuroscience, machine learning, and data engineering, contributing to cutting-edge research with real-world clinical and technological applications.
Key Responsibilities:
Lead and contribute to the development of robust language decoding models using:
Preprocessed (classical) fMRI datasets generated internally and sourced externally;
Raw k-space data, supporting the transition toward end-to-end modelling approaches as new data becomes available.
Design, implement, and optimise machine learning algorithms and pipelines, ensuring scalability, reproducibility, and high performance.
Produce high-quality individual contributions, including but not limited to:
Well-documented, production-ready code;
Peer-reviewed research publications and technical reports;
Internal documentation and knowledge-sharing materials;
Active participation in scientific conferences, workshops, and industry events.
Collaborate closely with cross-functional teams, including:
The modelling team, to align on architectures, methodologies, and evaluation strategies;
Data collection teams, to understand data generation processes and ensure optimal data usability;
Clinical and application teams, to translate research outputs into practical, real-world solutions.
Contribute to the overall scientific direction and strategic roadmap of the project by:
Identifying new research opportunities and proposing innovative approaches;
Staying up to date with the latest developments in relevant fields;
Supporting decision-making through technical insights and evidence-based recommendations.
Ensure adherence to best practices in research integrity, data governance, and ethical AI development.
Preferred Qualifications & Skills:
Strong background in machine learning, computational neuroscience, biomedical engineering, or a related field;
Experience working with neuroimaging data (e.g., fMRI) and/or signal processing (experience with k-space data is a plus);
Proficiency in programming languages such as Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow);
Proven track record of research contributions (publications, projects, or equivalent);
Strong communication and collaboration skills, with the ability to work effectively in multidisciplinary teams.
In the short to medium term, this role will primarily focus on advancing the development and optimisation of state-of-the-art language decoding models. The successful candidate will play a key role in designing, training, and evaluating models that leverage both classical fMRI datasets acquired by Karavela, as well as external datasets, and progressively incorporate raw k-space data as it becomes available through Karavela’s data collection efforts.
This position offers a unique opportunity to work at the intersection of neuroscience, machine learning, and data engineering, contributing to cutting-edge research with real-world clinical and technological applications.
Key Responsibilities:
Lead and contribute to the development of robust language decoding models using:
Preprocessed (classical) fMRI datasets generated internally and sourced externally;
Raw k-space data, supporting the transition toward end-to-end modelling approaches as new data becomes available.
Design, implement, and optimise machine learning algorithms and pipelines, ensuring scalability, reproducibility, and high performance.
Produce high-quality individual contributions, including but not limited to:
Well-documented, production-ready code;
Peer-reviewed research publications and technical reports;
Internal documentation and knowledge-sharing materials;
Active participation in scientific conferences, workshops, and industry events.
Collaborate closely with cross-functional teams, including:
The modelling team, to align on architectures, methodologies, and evaluation strategies;
Data collection teams, to understand data generation processes and ensure optimal data usability;
Clinical and application teams, to translate research outputs into practical, real-world solutions.
Contribute to the overall scientific direction and strategic roadmap of the project by:
Identifying new research opportunities and proposing innovative approaches;
Staying up to date with the latest developments in relevant fields;
Supporting decision-making through technical insights and evidence-based recommendations.
Ensure adherence to best practices in research integrity, data governance, and ethical AI development.
Preferred Qualifications & Skills:
Strong background in machine learning, computational neuroscience, biomedical engineering, or a related field;
Experience working with neuroimaging data (e.g., fMRI) and/or signal processing (experience with k-space data is a plus);
Proficiency in programming languages such as Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow);
Proven track record of research contributions (publications, projects, or equivalent);
Strong communication and collaboration skills, with the ability to work effectively in multidisciplinary teams.