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Stay abreast of latest AI trends and maintain state-of-the-art knowledge in machine learning, deep learning, and computational linguistics. Experience with machine learning techniques and tools including deep learning, reinforcement learning, and unsupervised learning.
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Python Proficiency : Expertise in building data ingestion tools using Python, including web scraping and external APIs, and proficient in Python data science packages (numpy, pandas, scikit-learn, nltk, TensorFlow, matplotlib, etc.
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Expert knowledge of Python programming and machine learning frameworks (Scikit-learn, TensorFlow, Keras, PyTorch, etc.) Strong understanding of fundamental computer science concepts, software design best practices, software development lifecycle and common machine learning design patterns.
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Expertise in at least one deep learning library - PyTorch, Tensorflow, JAX, keras required. Ampersand Biomedicines, Inc is looking for an enthusiastic and self-driven AI/ML Engineer with deep expertise in development of AI/Machine Learning/Deep Learning to join our team in developing a cutting-edge platform to identify and design new multi-specific medicines across a spectrum of therapeutic areas.
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We are looking for a rock star to join our team as a Machine Learning Engineer focused on protein design. To be effective in this role, you will need to be exceptional in structural biology, biophysics, and machine learning engineering.
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As a Machine Learning Engineer Co-Op, you will work closely with cross-functional teams, including Data Science, Software Engineering, and Product Management, to develop machine learning models, implement solutions, and ensure the successful deployment and maintenance of these models in production.
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The Algorithms, Machine Learning, & Data Science Group within AES Advanced Tech Team creates advanced algorithms in the fields of machine learning, artificial intelligence, signal processing, intelligent control, and other areas of electrical engineering and computer science that are of strategic interest to the AES Business Unit’s goals and roadmaps.
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Deploy machine learning models and applications on cloud platforms like Azure ML or Databricks, ensuring seamless integration, scalability, and cost-effectiveness. Strong proficiency in developing machine learning models using Python machine learning packages, Azure Databricks, and other Azure technologies.
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The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery.
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PhD in network science, physics, big data, behavior modeling, urban science, complex systems, machine learning, visualization, geospatial analysis or related field. By using large datasets of human behavior, tools and ideas from physics, applied mathematics, complex systems or network science, and collaborations with industry, government, and local communities, we seek not only to advance the understanding of the temporal dynamics of social systems to unprecedented levels but also to transform our findings into tools and policies to help achieve resilient and equitable adaptation of our societies.
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Drive cross-functional collaboration across our data science, machine learning, lab informatics, and medicinal chemistry teams to advance our computational infrastructure for our drug discovery and development mission.
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Bachelor's, Masters, or PhD degree preferred in Machine Learning, Robotics, Computer Science, Computer Engineering, Mechanical Engineering, Applied Mathematics, Statistics, or a related field.
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Extensive experience with Python Machine Learning toolsets (Tensorflow, PyTorch, Scikit-learn, Numpy, Pandas) 6+ years of professional experience as a data scientist or machine learning engineer with proven track record of delivering functional product oriented ML solutions.
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PhD in Computer Science, Artificial Intelligence, Computational Linguistics, or a related field. Strong programming skills in Python, and familiarity with AI frameworks like TensorFlow or PyTorch.
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Experience with analytic methods and technologies (artificial intelligence, machine learning/ deep learning/ neural networks, natural language processing, visualizations) Bachelor's degree in Computer Science, Applied Mathematics/ Data Sciences/ Data Analytics or related discipline required, advanced degree preferred.
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