YOUSSEF AMADGHOUS
Salé, Morocco
YOUSSEF AMADGHOUS
Academic Research & Scientific Writing Support
Category : Writer
I provide high-quality academic research support and scientific writing services for students, researchers, and professionals. With a Master’s degree in Chemical Sciences and ongoing PhD research in Brazil, I have extensive experience preparing academic papers, reports, presentations, and technical documents in fluent English.
I can help with:
1)Literature reviews and research summaries
2)Scientific writing (reports, essays, abstracts, posters, presentations)
3)Editing and proofreading for clarity, grammar, and structure
4)Data interpretation and discussion writing
5)Formatting according to journal or university guidelines
6)Visuals and scientific diagrams (ChemDraw, Illustrator)
Why choose me:
*Delivered an international conference oral presentation (Turin, 2024)
*Experienced in academic writing tutoring
*Strong command of English
*Reliable, detail-oriented, and fast communication
I can help with:
1)Literature reviews and research summaries
2)Scientific writing (reports, essays, abstracts, posters, presentations)
3)Editing and proofreading for clarity, grammar, and structure
4)Data interpretation and discussion writing
5)Formatting according to journal or university guidelines
6)Visuals and scientific diagrams (ChemDraw, Illustrator)
Why choose me:
*Delivered an international conference oral presentation (Turin, 2024)
*Experienced in academic writing tutoring
*Strong command of English
*Reliable, detail-oriented, and fast communication
Working hours
- Monday:08h00 To 18h00
- Tuesday:08h00 To 18h00
- Wednesday:08h00 To 18h00
- Thursday:08h00 To 18h00
- Friday:08h00 To 18h00
- Saturday:Not available
- Sunday:Not available
End-of-study project at Managem Group, Guemassa Mining Company, Marrakech, Morocco, under the theme: "Modeling Flotation Circuit for Predicting Grade and Recovery using Machine Learning (ML) Methods"
The steps of the methodology are as follows:
1)Collection and preprocessing of data and development of dataset
Definition of explanatory variables and variables to predict (grade and recovery)
2)Evaluation and comparison of the performances of supervised machine learning algorithms based on the prepared dataset.
3)Propose the most suitable ML model for predicting grade and recovery with lowest margin of error.
The steps of the methodology are as follows:
1)Collection and preprocessing of data and development of dataset
Definition of explanatory variables and variables to predict (grade and recovery)
2)Evaluation and comparison of the performances of supervised machine learning algorithms based on the prepared dataset.
3)Propose the most suitable ML model for predicting grade and recovery with lowest margin of error.
- 🇬🇧 English
- 🇫🇷 French
- 🇲🇦 Arabic
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