Internship - Natural Language Processing (Nlp) Research and Integration

**Integration of Natural Language Processing Methods into Medical Device**

**About Us**:
The iGlobe Scientific startup is an innovative Joint Venture established in 2023 through a collaboration between IHU Strasbourg and Medi-Globe Technologies, a German company renowned for its expertise in endoscopy, urology, and pneumology equipment. The startup is dedicated to developing cutting edge AI-based software for medical devices, with a particular focus on ultrasound imaging and diagnosis. By leveraging the strengths of both founding entities, our mission is to provide live assistance to clinicians, enhancing diagnostic accuracy and patient care.

Our company is based on the premises of IHU Strasbourg, a leading research and innovation center in France, dedicated to advancing image-guided medical procedures by using computer based assistance. This ecosystem offers unparalleled access to state-of-the-art facilities and equipment, fostering multidisciplinary collaboration with top experts in medicine, engineering, and data science.

**Internship Context Description**:
Recent advances in deep learning have revolutionized medical imaging and human-computer interaction. In this internship, we aim to explore how voice-based interfaces can be integrated into medical devices to enable intuitive, hands-free control by clinicians. Voice interaction is one of the most natural modalities for communication, and its adoption in high-stress clinical environments can significantly reduce cognitive load.

However, deploying such systems in sensitive healthcare settings requires strict adherence to privacy and security standards. To address this, we focus on edge computing solutions that process data locally, avoiding transmission to external servers. This introduces unique challenges in model efficiency, latency, and robustness—especially under constrained hardware conditions typical of embedded systems.

**Position Overview**:
We are seeking a motivated intern to join our R&D team and contribute to the development of edge-optimized NLP models. The role involves working on Speech-to-Text, Text Analysis, and Text to-Speech components tailored for embedded medical systems. You will engage with cutting edge technologies in deep learning and NLP and collaborate with experts across disciplines.

**Key Responsibilities**:

- Conduct a comprehensive literature review on NLP and Large Language Models (LLMs), with a focus on edge deployment strategies.
- Design and implement deep learning models for voice command processing, including wake-word detection, intent recognition, and command generation.
- Optimize models for performance on edge devices, considering constraints such as memory usage, inference latency, and energy efficiency.
- Evaluate model accuracy and reliability through experiments in simulated clinical environments.
- Collaborate with engineers, data scientists, and medical professionals to align technical development with real-world needs.
- Document findings and contribute to internal reports and potential scientific publications

**Required Skills**:

- Solid foundation in deep learning and NLP/LLMs.
- Proficiency in signal processing techniques and general computer science.
- Experience with programming languages such as Python and frameworks like TensorFlow or PyTorch.
- Strong analytical and problem-solving skills.
- Ability to work independently and collaboratively.
- Fluency in English (reading, writing, speaking).

**What We Offer**:

- An innovative and collaborative work environment.
- Competitive salary
- A cutting-edge infrastructure for AI model development, using our own dedicated GPU server and workstations
- Hands-on experience with state-of-the-art AI technologies in the medical field.
- Mentorship from experienced professionals in AI and medical imaging.
- Minimum 5 months - Maximum 6 months position

**Application Process**:
Join our dynamic team and help us shaping the future of intelligent medical technologies.

Type d'emploi : Stage
Durée du contrat : 6 mois

Rémunération : 700,00€ à 800,00€ par mois

Lieu du poste : En présentiel