Freelance Researcher – Communication Systems and AI
2 weeks ago
Design, implement, and evaluate intelligent models for communication system optimization and fault prediction using hybrid deep learning architectures. Develop reproducible, data-driven frameworks to enhance reliability, scalability, and performance in next-generation communication networks.
· Lead the design and simulation of deep learning–based frameworks for network performance enhancement and failure prediction.
· Develop Python-based modules integrating time-series, spatial, and environmental data for predictive communication analytics.
· Conduct simulation-driven experiments using benchmark datasets, realistic channel/noise models, and communication workloads.
· Publish results, including model architecture, evaluation metrics, and interpretability analysis, in peer-reviewed journals.
· Master's or Ph.D. in Electronics and Communication Engineering (ECE), Communication Systems or related fields.
· Strong background in wireless communication systems, signal processing, and machine learning.
· Proficiency with Python and deep learning frameworks such as TensorFlow and Keras.
· Programming: Python (mandatory)
· Communication Frameworks: Knowledge of 5G/6G system models, link-level simulators, or network-level performance tools.
· Minimum 2+ years of research or development experience in wireless communication systems, machine learning, or data-driven network analysis.
· Hands-on experience in LSTM, CNN, Attention, or hybrid deep learning architectures.
· Proven record of conducting and publishing reproducible research with strong experimental design and analysis skills.
· Deep understanding of radio communication principles, signal quality metrics (RSRP, SINR, RSRQ), and link-level modelling.
· Expertise in data-driven modelling using time-series and spatio-temporal datasets.
· Familiarity with evaluation metrics such as accuracy, F1-score, G-mean, and ROC-AUC.
· Ability to interpret deep learning models (e.g., using SHAP, attention maps) for explainability.
· Strong analytical and programming skills for implementing scalable and interpretable models.
· Develop, simulate, and validate intelligent frameworks for reliable communication system performance prediction.
· Implement hybrid deep learning architectures (e.g., LSTM, Attention, ConvLSTM) in Python for analysing communication datasets.
· Conduct experiments using benchmark datasets (e.g., ITU AI/ML in 5G Challenge) and realistic communication parameters.
· Benchmark proposed models against traditional and state-of-the-art baselines, analysing performance under dynamic environmental conditions.
· Ensure originality, reproducibility, and academic integrity across all research stages.
Contact :
Job Types: Part-time, Freelance, Volunteer
Contract length: 1 month
Pay: From ₹10,000.00 per month
Work Location: Remote
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