Mouhssine M.

Key Skills

Software

Don't disclose

Top Subject Matter

Medical imaging and diagnostic interpretation (radiology and laboratory findings)

Science education (biology/geology)

Top Data Types

Document

Image

Top Task Types

Diagnosis

Text Generation

Freelancer Overview

Clinical Clerk — CHU Ibn Rochd / Ibn Rochd University Hospital. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose, Microsoft Word, and Microsoft PowerPoint. Education includes Doctor of Medicine, Faculty of Medicine and Pharmacy of Casablanca (FMPC) (2020) and Clinical Clerkships, Ibn Rochd University Hospital (CHU Ibn Rochd) (2022). AI-training focus includes data types such as Medical, DICOM, and Document and labeling workflows including Diagnosis and Text Generation.

Labeling Experience

Science Teacher (Evening Position) — Middle School Science

DocumentText Generation

Planned and delivered science lessons requiring structured explanation of scientific concepts for learners. While the resume does not mention AI or labeling, the teaching activity supports skills relevant to creating AI training or instructional annotation content. The work involved producing lesson material and communicating concepts clearly. • Planned engaging lessons covering biology and geology. • Simplified complex scientific concepts for learners with different abilities. • Produced and organized teaching content for recurring sessions. • Practiced communication and presentation skills for educational delivery.

2022 - Present

Clinical Clerk — CHU Ibn Rochd / Ibn Rochd University Hospital

Don't discloseDiagnosis

Assisted with interpreting laboratory investigations and medical imaging to support clinical decision-making during daily patient management. This work involved reviewing clinical imaging and diagnostic results and relating them to suspected conditions for differential diagnosis and reasoning. The exposure aligns with medical annotation-style tasks commonly used in AI datasets for diagnostic support. • Interpreted radiological findings (X-ray, CT, MRI) to correlate with patient presentation. • Used differential diagnosis formulation and clinical reasoning based on investigations. • Supported care teams with documentation and diagnostic interpretation. • Worked across multiple specialties including radiology, emergency, ICU, and oncology.

2022 - Present

Education

Work History