AI Specialist - Healthcare

📌 𝗗𝗲𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻:

We are seeking a highly motivated and innovative AI Specialist to join our pioneering healthcare technology team. This role is pivotal in developing and deploying cutting-edge artificial intelligence and machine learning solutions that directly impact patient outcomes and clinical efficiency. You will be responsible for the end-to-end lifecycle of clinical AI models, from conceptualization and data analysis of complex healthcare datasets to model validation and integration into clinical workflows. Collaborating closely with clinicians, data scientists, and engineers, you will tackle some of the most challenging problems in medicine, such as predictive diagnostics and personalized treatment planning. Your work will ensure our solutions adhere to the highest ethical and regulatory standards, including HIPAA and FDA guidelines. If you are passionate about leveraging AI to revolutionize healthcare and improve lives, this is the opportunity for you. Join us in shaping the future of medicine.

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🎯 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀:

▸ Proven experience in developing and validating machine learning models using Python and common libraries (e.g., Scikit-learn, Pandas, NumPy).

▸ Hands-on expertise with deep learning frameworks such as TensorFlow or PyTorch.

▸ Demonstrated experience working with diverse healthcare data modalities, including Electronic Health Records (EHR), medical imaging (DICOM, NIfTI), and/or genomic data.

▸ Strong understanding of statistical analysis, predictive modeling, and machine learning algorithms.

▸ Knowledge of healthcare data privacy and security regulations, particularly HIPAA.

▸ Familiarity with tools and libraries for medical data analysis (e.g., MONAI, SimpleITK, GATK).

▸ Experience with the full ML lifecycle, from data preprocessing and feature engineering to model deployment and monitoring.

▸ Bachelors or Masters degree in Computer Science, Data Science, Biomedical Engineering, or a related field.

✨ 𝗗𝗲𝘀𝗶𝗿𝗮𝗯𝗹𝗲𝘀:

▸ PhD in a relevant field with a focus on machine learning in healthcare.

▸ Record of peer-reviewed publications or presentations at relevant scientific conferences (e.g., NeurIPS, ICML, RSNA, AMIA).

▸ Experience with MLOps and deploying models in a cloud environment (AWS, GCP, Azure).

▸ Experience with clinical validation processes and collaborating with clinical teams for model integration.

▸ Familiarity with regulatory pathways for AI/ML-based Software as a Medical Device (SaMD).

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🚀 𝗧𝗮𝗸𝗲 𝘁𝗵𝗲 𝗟𝗲𝗮𝗽 𝗧𝗼𝘄𝗮𝗿𝗱 𝗮𝗻 𝗘𝘅𝗰𝗶𝘁𝗶𝗻𝗴 𝗙𝘂𝘁𝘂𝗿𝗲 – 𝗔𝗽𝗽𝗹𝘆 𝗡𝗼𝘄! 🚀