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Causal Machine Learning, Causal Inference, Causal Discovery, Counterfactual, Causal Deep Learning, Causal Structure, Structure Learning, Structure Equation Model, SEM, Explainable AI, XAI, Data Science, Deep Learning, R, Python, Julia, Bioinformatics, Multiomics, Integrative Analysis, Medicine, Actigraphy, Pregnancy, Precision Medicine, Personalized Medicine, EHR, Electronic Health Records.
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Our client is a pioneer within the programmable RNA medicine space and are looking for an expert of Machine Learning, Artificial Intelligence, and RNA Biology to help shift the paradigm of novel drug development.
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Machine Learning and Deep Learning (Some or all): Deep neural networks(CNN, RNN, LSTM), Supervised methods such as Tree based models (random forest, xgboost, Light GBM), K-NN, SVM as well as Unsupervised methods such as Clustering (Hierarchical, K-mean, K-medoids), Dimensionality reduction (PCA.
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You have previous Individual contributor experience in both data engineering and machine learning engineering for deep learning models, preferably in a scientific application.
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Experience developing AI and deep learning-based machine vision metrology applications where defects can be trained using simple UI’s. 2+ years of hands-on experience with machine vision systems in a PCB, Consumer Electronics, Automotive or similar field.
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As a Vice President, Data Science Lead for Finance and Actuarial, you will partner with Machine Learning Engineers, Data Engineers, Data Analysts and other specialists to transform financial and actuarial processes by building state-of-the-art actuarial, financial, and behavioral models.
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Founded in 2011, we have a long history of delivering tech-forward web/cloud, robotic, IoT, and machine learning solutions. Machine Learning (ML) and Computer Vision (CV) We’re constantly working on new projects that will push you and keep you always learning new technologies.
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San Francisco, California (Hybrid On-Site): $248,700 - $283,800 for Sr. Lead Machine Learning Engineer. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Lead Machine Learning Engineer.
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Implement data preprocessing and feature engineering techniques to ensure high-quality input for machine learning models. Proficient in Python and relevant machine learning frameworks (e.g., PyTorch, TensorFlow, Hugging Face.
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6 to 10 years of professional experience in predictive modeling, data science, machine learning. Hands on experience with explainable machine learning, e.g., Shapley.
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A Glimpse into the Daily Routine of a Machine Learning Engineer. Self-motivated and proactive, with a passion for learning and staying updated with the latest trends and advancements in the field of data engineering.
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Familiarity with AI platforms, tools, and frameworks, such as machine learning algorithms, natural language processing, and computer vision. Proficiency in using authoring tools such as Articulate Storyline, Adobe Captivate, or similar software to develop interactive e-learning content.
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PiLog is a leading provider of state-of-the-art solutions focused on creating a common business language and managing the rules for creating high-quality, multilingual terminology using Machine Learning and Artificial Intelligence technologies.
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Successful candidates will work closely with the Computational Chemistry, Machine Learning and Application Engineering teams to tap into the wealth of evolutionary, structural and -omics data to unlock the full potential of unified machine learning representations and large-scale geometric deep learning generative models.
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Responsibilities: Extract key physics results from data across diagnostics related to machine operation and performance. This role involves forging relationships with people across R&D to synthesize an overall physical picture of machine performance and plasma dynamics.
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machine learning jobs Title: sr data scientist Company: Microsoft in New York, NY
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When Rage Applying Strikes: How to Identify Unserious Candidates
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