Graph Architect - Neoj

Overview :We are seeking a Graph Architect with specialized expertise in graph-based data models and algorithms, focusing particularly on the use of cliques and other complex graph structures for mental health disease prediction and causality analysis. This role is central to our efforts to leverage graph technology to uncover insights into the intricate networks of factors contributing to mental health conditions, facilitating the development of predictive models and causal analysis tools.Key Responsibilities :- Design and implement graph-based architectures utilizing Neo4j or similar graph databases, focusing on modelling complex relationships in mental health data to identify cliques and other significant graph structures.- Develop and optimize algorithms for the detection and analysis of cliques within large-scale mental health datasets, aiming to identify key patterns and predictors of mental health issues.- Work closely with data scientists and healthcare professionals to translate clinical and research questions into graph-based analysis strategies, leveraging cliques for deeper insights into mental health causality and prediction.- Lead the integration of graph technology with other AI models, including Alpha Tensor and AlphaFold architectures, to enhance the predictive power and accuracy of mental health disease models.- Stay abreast of the latest developments in graph theory and graph databases, especially as they relate to healthcare and mental health applications, ensuring our solutions remain at the cutting edge of technology.- Guide the ethical use of graph-based models in mental health data analysis, emphasizing data privacy, security, and the responsible interpretation of findings.Qualifications :- Master's or PhD in Computer Science, Data Science, Bioinformatics, or a related field, with a focus on graph theory, graph databases, and their applications.- Demonstrated expertise in graph database technologies, such as Neo4j, and a deep understanding of graph structures, particularly cliques, and their relevance to data analysis.- Experience in designing and implementing graph-based solutions for complex data analysis, preferably in healthcare or mental health contexts.- Strong programming skills in languages and frameworks relevant to graph databases and AI (e.g., Python, Java, Cypher, TensorFlow, Py Torch).- Familiarity with machine learning and AI principles and how they can be applied in conjunction with graph-based data models to solve complex problems.- Excellent analytical and problem-solving skills, with the ability to conceptualize and execute innovative data analysis strategies.Preferred Skills :- Background or keen interest in mental health, psychology, or related fields, with an understanding of the data challenges and opportunities in this domain.- Published research or significant projects that demonstrate the application of graph theory to real-world problems, particularly in healthcare or mental health. (ref:hirist.tech)