Requirements

Master’s or PhD in Data Science, Genomics, Bioinformatics, or a related field.
5+ years of experience in AI/ML, with a focus on genomics or personalised medicine.
Strong experience in handling large-scale healthcare datasets and genomic data.
Extensive experience in various AI applications, including chatbots, large language models (LLMs), image analysis, generative AI, and predictive AI.
Proficiency in programming languages like Python, R, and machine learning frameworks (e.g., TensorFlow, PyTorch).
Familiarity with bioinformatics tools and databases.
Knowledge of healthcare regulations related to genomic data handling.
Excellent problem-solving, analytical, and communication skills

Key Responsibilities

Develop AI models that incorporate genomic, clinical, and other healthcare data.
Use machine learning techniques to identify patterns and trends in genetic data for personalised healthcare interventions.
Collaborate with clinical experts to interpret genomic data and design experiments.
Build and deploy predictive models that assist in personalised medicine, such as risk assessments, diagnostics, and treatment recommendations.
Stay updated with advancements in genomics and bioinformatics and implement relevant techniques in AI model development.
Ensure genomic data privacy, security, and compliance with regulations (e.g., GDPR, HIPAA).
Collaborate with data engineers to develop and optimise data pipelines for large-scale genomic datasets.
Present findings and models to cross-functional teams, clinical stakeholders, and external partners.

Skills: tensorflow,aiml,chatbots,ml,image analysis,pytorch,problem-solving,predictive ai,r,large language models (llms),large-scale healthcare datasets,generative ai,bioinformatics tools,analytical skills,machine learning,python,ai/ml,genomics,data,healthcare regulations,communication skills,personalised medicine

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