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I am a machine learning researcher and engineer with over a decade of hands-on experience applying ML and deep learning to medical imaging, neuroscience, and electrochemical systems. I enjoy designing scalable models, building robust data pipelines, and driving reproducible ML workflows in high-impact research settings. My work spans large-scale model training, representation learning, generative approaches, and LLM-assisted data workflows. I am proficient with Python, Linux, distributed computing, and collaborating across disciplines to turn complex data into actionable insights.…I am a machine learning researcher and engineer with over a decade of hands-on experience applying ML and deep learning to medical imaging, neuroscience, and electrochemical systems. I enjoy designing scalable models, building robust data pipelines, and driving reproducible ML workflows in high-impact research settings. My work spans large-scale model training, representation learning, generative approaches, and LLM-assisted data workflows. I am proficient with Python, Linux, distributed computing, and collaborating across disciplines to turn complex data into actionable insights.

Amir Omidvarnia

Data Scientist, AI Engineer, AI Developer, +1

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I am a machine learning researcher and engineer with over a decade of hands-on experience applying ML and deep learning to medical imaging, neuroscience, and electrochemical systems. I enjoy designing scalable models, building robust data pipelines, and driving reproducible ML workflows in high-impact research settings. My work spans large-scale model training, representation learning, generative approaches, and LLM-assisted data workflows. I am proficient with Python, Linux, distributed computing, and collaborating across disciplines to turn complex data into actionable insights.…I am a machine learning researcher and engineer with over a decade of hands-on experience applying ML and deep learning to medical imaging, neuroscience, and electrochemical systems. I enjoy designing scalable models, building robust data pipelines, and driving reproducible ML workflows in high-impact research settings. My work spans large-scale model training, representation learning, generative approaches, and LLM-assisted data workflows. I am proficient with Python, Linux, distributed computing, and collaborating across disciplines to turn complex data into actionable insights.

Available to hire

I am a machine learning researcher and engineer with over a decade of hands-on experience applying ML and deep learning to medical imaging, neuroscience, and electrochemical systems. I enjoy designing scalable models, building robust data pipelines, and driving reproducible ML workflows in high-impact research settings.

My work spans large-scale model training, representation learning, generative approaches, and LLM-assisted data workflows. I am proficient with Python, Linux, distributed computing, and collaborating across disciplines to turn complex data into actionable insights.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Senior Researcher – Machine Learning & Data Science at Forschungszentrum Jülich, Department of Theoretical Electrochemistry and Data Science

January 1, 2024 - Present

Design and training of deep learning models for electrochemical image analysis in battery research; Development of U-Net–based segmentation pipelines for microscopy and imaging diagnostics; Synthetic data generation using DCGANs and diffusion-based models to augment scarce experimental datasets; LLM-assisted image segmentation and annotation workflows for domain-specific scientific images; End-to-end ML pipelines covering data preprocessing, training, inference, and evaluation.

Senior Researcher – Applied Machine Learning at Institute of Neuroscience and Medicine, Forschungszentrum Jülich, Germany

January 1, 2021 - January 1, 2024

Large-scale ML modeling on UK Biobank data (>500k subjects) for prediction and representation learning; Training and benchmarking of ML models on high-performance clusters using HTCondor and SLURM; Development of scalable Python-based ML pipelines under Linux environments; Statistical evaluation and robustness analysis of predictive models.

Marie Curie Research Fellow – Medical Image Processing at EPFL, Switzerland

January 1, 2019 - January 1, 2021

Deep learning and nonlinear modeling of fMRI time series; Feature learning and representation analysis for large neuroimaging datasets; Cross-site reproducible ML experimentation.

Postdoctoral Researcher – Machine Learning for Medical Data at University of Melbourne, Australia

January 1, 2014 - January 1, 2019

ML-driven analysis of EEG, fMRI, and PET data at scale; Algorithm design for detection, segmentation, and temporal modeling of biomedical signals; End-to-end research pipelines from data acquisition to model validation.

Senior Researcher – Applied Machine Learning at Forschungszentrum Jülich, Institute of Neuroscience and Medicine

January 1, 2021 - January 1, 2024

Large-scale ML modeling on UK Biobank data (>500k subjects) for prediction and representation learning; training and benchmarking of ML models on high-performance clusters using HTCondor and SLURM; development of scalable Python-based ML pipelines under Linux environments; statistical evaluation and robustness analysis of predictive models.