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The division consists of nine faculty members in a high-volume clinical service overseeing and interpreting studies across the spectrum of neuroimaging performed at our Center City and South Philadelphia campuses, as well as state-of-the-art suburban outpatient imaging centers. The Department boasts a highly regarded residency program with forty residents, and the division maintains an ACGME-accredited neuroradiology fellowship with four fellows, along with an additional three combined MSK/neuro MRI fellows. The division collaborates closely with neurosurgery, orthopedic surgery, otolaryngology, neurology, ophthalmology, rehabilitation medicine and psychiatry, as well as research PhDs within the department. There are ample opportunities for clinical research in a variety of areas as well as unique expertise in Health Policy research. There are also research and development opportunities with our departmental machine learning/artificial intelligence group, data science and Imaging Informatics.
Excellent coding and design skills, particularly in Java/Scala and Python and or Java.. Experience in AWS technologies such as EC2, Redshift, Cloud formation, EMR, AWS S3, AWS Analytics required.. Big data related AWS technologies like HIVE, Presto, Hadoop required.. AWS certification is preferable: AWS Developer/Architect/DevOps/Big Data. Excellent working knowledge of Apache Hadoop, Apache Spark, Kafka, Scala, Python etc.
+ Bachelor's or Master's degree or equivalent experience and a shown foundation in statistical and data science (e.g. Machine Learning, Predictive analytics, etc.). + Skill with analytic tools ranging from relational databases and SQL to Excel, and Python/R. Experience with Product analytics tools like Amplitude, Content square, Adobe analytics, etc.. + Experience working with on Premise and/or Cloud analytics environments like Hadoop, AWS, Snowflake, etc.. + Experience with data visualization and enablement tools like Tableau, Power BI, etc.
As a leader in real-world evidence (RWE) and data-driven technology, ConcertAI partners with top pharmaceutical companies, healthcare providers, and research institutions to enhance patient outcomes and streamline clinical research. By leveraging evidence-generation and artificial intelligence, we deliver unparalleled insights into treatment effectiveness, patient care, and disease progression to advance precision medicine and medical innovation. Design and build prototype machine learning (ML) and deep learning (DL) models to extract actionable insights from complex, multimodal real-world data, including EHR, claims, clinical notes, genomics, and transcriptomics data. Proficiency in one or more machine learning and deep learning frameworks such as scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, or Hugging Face Transformers, and in data visualization tools like matplotlib, seaborn, Plotly, or Streamlit for exploratory analysis and interactive reporting. Python (required), R (preferred), SQL (Snowflake, BigQuery), Jupyter, Git, Docker, Bash
Design and maintain fraud rules and scoring logic for transaction monitoring systems. Ensure alignment with regulatory expectations, model risk governance, and internal audit requirements. Explore and implement new technologies (e.g., graph analytics, behavioral biometrics, NLP) for advanced fraud detection. Strong command of Python, R, SQL, and data science libraries (pandas, scikit-learn, TensorFlow, etc.. Exposure to real-time fraud systems (e.g., SAS Fraud Management, Actimize, Falcon, etc.)
A company at the intersection of AI and Life Sciences is looking to expand their highly successful AI Research team.. The company is based in the San Francisco Bay Area, but the role may be open to fully remote.. Libriaries: PyTorch, Tensorflow, Scikit-learn, Pandas. Neural Networks: Graph Neural Networks, CNN. Protein Language Models: AlphaFold, etc.
🚀 Publish, present, and patent high-impact findings in AI and machine learning.. Conduct cutting-edge research in artificial intelligence, including areas such as natural language processing, computer vision, generative models, and reinforcement learning.. Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ACL, CVPR, ICLR) is highly preferred.. Expertise in machine learning, deep learning, or statistical modeling.. Experience with model development using TensorFlow, PyTorch, JAX, or similar frameworks
Broad technical foundation in software engineering and deep learning (through self-study, practical experience, or PhD).. ML: knows the theory and applied side of deep learning, especially computer vision and foundational model architectures (PyTorch, OpenCV, Tensorflow).. Backend: experience designing and building scalable and high availability server-side systems (Python, NodeJS, or Golang).. Cloud: familiarity with DevOps and infrastructure (i.e. Docker, Kubernetes, GPU scheduling) on cloud (i.e. GCP, AWS).. Monitoring: experience with logging systems and monitoring tools such as DataDog, Sentry, and/or CloudWatch
Fully Remote (onsite in Vinings, GA from Mon-Thurs if converted to FTE). We are seeking a Senior BI Analyst with expertise in Python, SQL, Tableau, and predictive analytics.. You will work with large datasets across SAP and Snowflake environments to deliver strategic insights, with a strong focus on forecasting container arrivals, optimizing inventory levels, and identifying cost-saving opportunities – all in support of a major ERP modernization and the nationwide consolidation of distribution centers.. System Migration : Lead data analysis and reporting for a major migration from a legacy ERP to SAP Warehouse Management, with reporting transitioning to Snowflake.. Python Predictive Analytics : Perform predictive modeling in Python to forecast container arrivals, inventory levels, and other supply chain KPIs.
Develop and execute comprehensive technical and business strategy for all data science, data engineering, and business intelligence initiatives.. Design and implement scalable data pipelines and ETL processes using modern cloud platforms (Databricks, Snowflake).. Knowledge of modern data engineering tools and cloud platforms (Python, Qlik, SQL, Databricks, Snowflake).. As a federal contractor that engages in safety-sensitive work, AmeriGas cannot permit employees in certain positions to use medical marijuana, even if prescribed by an authorized physician. Similarly, applicants for such positions who are actively using medical marijuana may be denied hire on that basis.
Seeking a Machine Learning Engineer to maintain, enhance, and productionize an existing predictive model that estimates the average duration of construction jobs.. You’ll work with historical workflow data, improve model accuracy, and explore new ML opportunities once the current model is stable.. Python – strong proficiency for data manipulation & model implementation.. Applied Machine Learning – hands-on experience with regression, classification, or similar predictive modeling techniques.. Work with historical workflow data to refine accuracy and reliability.