I am an AI PhD candidate and R&D engineer with a strong background in data science, Python engineering, and applied machine learning for scientific and industrial problems. My experience covers the full data and AI workflow: data processing, structuring, validation, quality control, automation, model development, benchmarking, and performance analysis. I mainly work with Python, PyTorch, Graph Neural Networks, experiment tracking tools, and high-performance computing environments. I am open to a broad range of data-related roles, including data science, data management, data quality, analytics, automation, AI engineering, and research-oriented software development. I particularly enjoy projects that require reliable pipelines, clean code, reproducible workflows, and rigorous technical analysis. I actively use and evaluate recent agentic AI tools to accelerate software development, improve experimentation workflows, and support code quality, testing, documentation, and productivity. I am also currently learning Rust to better understand systems-level performance optimization and to explore faster components for Python-based data and scientific computing pipelines.

Nathan CHANEZ

I am an AI PhD candidate and R&D engineer with a strong background in data science, Python engineering, and applied machine learning for scientific and industrial problems. My experience covers the full data and AI workflow: data processing, structuring, validation, quality control, automation, model development, benchmarking, and performance analysis. I mainly work with Python, PyTorch, Graph Neural Networks, experiment tracking tools, and high-performance computing environments. I am open to a broad range of data-related roles, including data science, data management, data quality, analytics, automation, AI engineering, and research-oriented software development. I particularly enjoy projects that require reliable pipelines, clean code, reproducible workflows, and rigorous technical analysis. I actively use and evaluate recent agentic AI tools to accelerate software development, improve experimentation workflows, and support code quality, testing, documentation, and productivity. I am also currently learning Rust to better understand systems-level performance optimization and to explore faster components for Python-based data and scientific computing pipelines.

Next availability:
July 1, 2026

I am an AI PhD candidate and R&D engineer with a strong background in data science, Python engineering, and applied machine learning for scientific and industrial problems.

My experience covers the full data and AI workflow: data processing, structuring, validation, quality control, automation, model development, benchmarking, and performance analysis. I mainly work with Python, PyTorch, Graph Neural Networks, experiment tracking tools, and high-performance computing environments.

I am open to a broad range of data-related roles, including data science, data management, data quality, analytics, automation, AI engineering, and research-oriented software development. I particularly enjoy projects that require reliable pipelines, clean code, reproducible workflows, and rigorous technical analysis.

I actively use and evaluate recent agentic AI tools to accelerate software development, improve experimentation workflows, and support code quality, testing, documentation, and productivity. I am also currently learning Rust to better understand systems-level performance optimization and to explore faster components for Python-based data and scientific computing pipelines.

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Language

French
Fluent
English
Advanced
Japanese
Beginner

Work Experience

PhD Candidate & R&D Engineer in Artificial Intelligence at STMicroelectronics / Université Grenoble Alpes (CIFRE Thesis)
March 1, 2023 - November 22, 2025
Development & Scaling (HPC): Design and optimization of Deep Learning architectures (PyTorch). Scaling training processes on computing clusters (job management via LSF, multi-GPU parallelization). Algorithm development. Graph Neural Networks, Surrogate models. Methodology & Analysis: Implementation of robust validation pipelines and model performance monitoring (experiment tracking, metric analysis, benchmarking). Innovation & Valorization: Internal patent filings, Scientific communication (presentations at AEET2025 and ICPECA2026 conferences). Leadership & Knowledge Transfer: Technical mentoring of interns and new hires. Promoting Python development best practices within the team.
Deep Learning Engineer (Internship + Fixed-Term Contract) at STMicroelectronics (Crolles)
March 31, 2023 - March 31, 2023
Upskilling & PhD Preparation: Acquisition of expertise in Deep Learning and structuring of the work environment. Immersion Internship - Partnership Platform ENSMM/SEDIS: Python image processing, OpenCV, Predictive maintenance.
Intern at Immersion Internship - Partnership Platform ENSMM/SEDIS
July 1, 2021 - July 1, 2021
Python image processing, OpenCV, Predictive maintenance.
Academic Tutor at Besançon (25)
January 1, 2022 - January 1, 2022
Tutoring up to 8 students per week (Middle school to BTS level) in scientific and literary subjects.
Army Reservist at French Army
January 1, 2020 - January 1, 2020
Army-specific missions and training. Stress resistance, decision-making efficiency, team management.
Deep Learning Engineer (Internship + Fixed-Term Contract) at STMicroelectronics (Crolles)
March 1, 2023 - March 1, 2023
Upskilling in Deep Learning and structuring of the work environment for research deployment. Developed hands-on DL solutions and contributed to project-oriented tasks during the internship and fixed-term period.
Immersion Internship - Partnership Platform at ENSMM/SEDIS
July 1, 2021 - July 1, 2021
Python image processing, OpenCV, Predictive maintenance.
PhD Candidate & R&D Engineer in Artificial Intelligence at STMicroelectronics / Université Grenoble Alpes (CIFRE Thesis)
March 1, 2023 - November 23, 2025
Development and scaling of Deep Learning architectures (PyTorch) and HPC-based training on computing clusters (LSF, multi-GPU). Algorithm development including Graph Neural Networks and surrogate models. Implement robust validation pipelines and model performance monitoring. Involved in internal patent filings and scientific communication (AEET2025, ICPECA2026). Mentoring interns and new hires; promoting Python development best practices within the team.
Immersion Internship at Partnership Platform ENSMM/SEDIS
July 1, 2021 - July 1, 2021
Python image processing, OpenCV, Predictive maintenance.
Deep Learning Engineer (Internship + Fixed-Term Contract) at STMicroelectronics (Crolles)
February 1, 2022 - March 31, 2023
Upskilling & PhD Preparation: Acquisition of expertise in Deep Learning and structuring of the work environment.
Academic Tutor at Besançon (25)
January 1, 2019 - January 1, 2022
Tutoring up to 8 students per week (Middle school to BTS level) in scientific and literary subjects.
Army Reservist at French Army
January 1, 2016 - January 1, 2020
Army-specific missions and training. Stress resistance, decision-making efficiency, team management.

Education

PhD in Artificial Intelligence at Grenoble / Crolles
March 1, 2023 - March 1, 2026
Double Degree: Master in Microsystems, Embedded Instrumentation, and Robotics at Université de Franche-Comté
January 1, 2021 - January 1, 2022
Engineering Degree (Microsystems & Embedded Instrumentation) at École Nationale Supérieure de Mécanique et des Microtechniques - Besançon
January 1, 2019 - January 1, 2022
CPGE (Preparatory Classes for Grandes Écoles) at Lycée Jules Haag, Besançon
January 1, 2016 - January 1, 2019
PhD in Artificial Intelligence at Grenoble / Crolles (CIFRE Thesis with STMicroelectronics and Université Grenoble Alpes)
March 1, 2023 - March 1, 2026
Master in Microsystems, Embedded Instrumentation, and Robotics (Double Degree) at Université de Franche-Comté
January 1, 2021 - January 1, 2022
Engineering Degree (Microsystems & Embedded Instrumentation) at École Nationale Supérieure de Mécanique et des Microtechniques - Besançon
January 1, 2019 - January 1, 2022
CPGE (Preparatory Classes for Grandes Écoles) at Lycée Jules Haag, Besançon
January 1, 2016 - January 1, 2019
PhD in Artificial Intelligence at Grenoble / Crolles (CIFRE Thesis with STMicroelectronics and Université Grenoble Alpes)
March 1, 2023 - March 1, 2026
Double Degree: Master in Microsystems, Embedded Instrumentation, and Robotics at Université de Franche-Comté
January 1, 2021 - January 1, 2022
Engineering Degree (Microsystems & Embedded Instrumentation) at École Nationale Supérieure de Mécanique et des Microtechniques - Besançon
January 1, 2019 - January 1, 2022
CPGE (Preparatory Classes for Grandes Écoles) at Lycée Jules Haag, Besançon
January 1, 2016 - January 1, 2019
PhD in Artificial Intelligence at Grenoble / Crolles (CIFRE)
March 1, 2023 - March 1, 2026
Double Degree: Master in Microsystems, Embedded Instrumentation, and Robotics at Université de Franche-Comté
January 1, 2021 - January 1, 2022
Engineering Degree (Microsystems & Embedded Instrumentation) at École Nationale Supérieure de Mécanique et des Microtechniques - Besançon
January 1, 2019 - January 1, 2022
CPGE (Preparatory Classes for Grandes Écoles) at Lycée Jules Haag, Besançon
January 1, 2016 - January 1, 2019

Qualifications

Add your qualifications or awards here.

Industry Experience

Computers & Electronics, Software & Internet, Professional Services, Manufacturing, Education, Media & Entertainment