Graduate Research Assistant (ML & Scientific Writing)

Offre de Stage

Position: Graduate Research Assistant (Machine Learning & Scientific Writing)
Location: Remote (Morocco)
Compensation: 600 MAD/month
Duration: 3 Months (Immediate)

About Our Research Portfolio
Our research group operates at the intersection of applied machine learning, computer vision, and responsible AI policy. We are currently advancing four major research tracks aimed at high-profile UK research grants and top-tier international publications:

Computer Vision for Ecosystem Protection: Building an identity-verification system based on structural biometrics using Siamese Networks and Triplet Loss to track timber supply chains.
Algorithmic Fairness Public Engagement: Constructing synthetic data engines and interactive games exploring public perceptions of AI-driven credit/employment classification.
Accountable AI Governance: Investigating how public frameworks use automated decision-making and how legal principles can optimise public service delivery.
Deep Learning for Aquaponics Eco-Systems: Fine-tuning Hybrid LSTM-Autoencoders and 1D Convolutional temporal architectures to model complex water dynamics and predict anomalies.

Required Skill Sets
1. Technical Machine Learning Stack
Proficient in Python and major deep learning libraries (PyTorch or TensorFlow/Keras).
Hands-on experience with hyperparameter tuning, grid search, and k-fold cross-validation.
Familiarity with time-series architectures (LSTM/GRU) or computer vision/embedding backbones is highly advantageous.
2. Academic & Writing Excellence
Exceptional Literary Command: Outstanding capability to read, digest, and synthesise complex scientific papers. You must be able to draft clean, logical, and academically rigorous prose.
Publication Track Record: Must have submitted or successfully published at least one peer-reviewed research paper, workshop paper, or university thesis.
3. LaTeX / Overleaf (Optional Bonus): Experience typesetting manuscripts or managing citations in LaTeX/Overleaf is a fantastic plus! However, this is strictly optional—if you are an exceptional scientific writer comfortable in Word or Google Docs, we warmly encourage you to apply.

✉️ How to Apply
Please fill out this Google Form with the following attachments:
Your updated CV/Resume highlighting relevant ML projects.
A link or PDF copy of your best written or published research sample.
A brief, 3-sentence note detailing your experience with hyperparameter optimisation or model tuning.

https://forms.gle/wkCh7kje43S8w5o36