Research and Development: Lead the research, design, and implementation of advanced NLP algorithms and models to extract structured information from unstructured scholarly content, including academic papers, articles, and research datasets.
Text Processing and Analysis: Develop robust pipelines for text preprocessing, feature extraction, and semantic analysis to enable effective search, summarization, and classification of academic literature.
Information Retrieval and Recommendation Systems: Design and optimize algorithms for content recommendation, citation analysis, and personalized user experiences based on NLP-driven insights.
Model Evaluation and Optimization: Conduct rigorous experimentation and performance evaluation of NLP models, leveraging techniques such as cross-validation, hyperparameter tuning, and benchmarking against industry standards.
Collaboration and Communication: Collaborate closely with product managers, software engineers, and domain experts to integrate NLP solutions into the ScholarLink platform, and effectively communicate technical concepts and findings to non-technical stakeholders.
Continuous Learning and Innovation: Stay abreast of the latest developments in NLP research, methodologies, and tools, and proactively identify opportunities to apply emerging techniques to enhance ScholarLink’s capabilities.
Requirements & Skills:
Ph.D. or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field, with a strong focus on NLP.
Proven track record of 5+ years of experience in designing and implementing NLP algorithms and models, preferably in a research or industry setting.
Expertise in machine learning frameworks such as TensorFlow, PyTorch, or sci-kit-learn, and proficiency in programming languages such as Python or R.
Solid understanding of NLP techniques and methodologies, including text mining, sentiment analysis, entity recognition, topic modeling, and word embedding.
Experience with large-scale data processing tools and platforms, such as Apache Spark, Hadoop, or AWS/GCP/Azure services.
Strong analytical and problem-solving skills, with the ability to translate complex research concepts into practical, scalable solutions.
Excellent communication and collaboration skills, with the ability to work effectively in a fast-paced, interdisciplinary team environment.
Publications or contributions to the NLP research community, such as papers, patents, or open-source projects, would be a plus.
