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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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We're looking for a medicinal chemist to drive our drug discovery projects, who is also excited about partnering with machine learning scientists and software developers to advance our computational platforms that accelerate compound design and synthesis.
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Advances in bigchemical data, massive computing power, artificial intelligence, andmolecular dynamics simulation are changing the way we develop newdrugs.
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Keywords: Cheminformatics, Computational Chemistry, Machine Learning, Artificial Intelligence, Computational Sciences, Drug Discovery, Pharmaceutical, Biotechnology, Boston, Cambridge, Massachusetts.
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The Bioinformatics Scientist is responsible for analyzing antibody selection data from yeast display, implementing machine learning algorithms to enhance data analysis and lead selection, and managing the data pipeline from raw file processing to database storage.
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Our backend codebase depends primarily on Ruby, Rails, PostgreSQL, Algolia, Docker, Redis, and whatever comes next. As a Software Engineer on our Learning team, you will be building out interactivity and interoperability features to give learners the best-in-class experience.
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We are growing a team of people from multiple disciplines who love solving complex problems with data and are excited by the prospect of creating the brains behind Iris. As a Machine Learning Engineer, you will be responsible for building the infrastructure and implementing the algorithms that make Iris smart.
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The ideal candidate has a machine learning background, with previous experience building large-scale generative models, complex pre-processing pipelines, and comprehensive benchmarks to support scientific tasks.
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For methods builders we also welcome links to github/bitbucket pages, and relevant bioinformatics/computational biology/machine learning community contributions. The position aims for candidates with a strong quantitative and computational background with extensive experience in genomics/transcriptomics (analysis of different bulk/single cell/spatial Next Generation sequencing Techniques as well as development of novel methods.
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The team leverages its experience in the fields of signal processing, computer vision, computational linguistics, machine learning, artificial intelligence, communication systems, and other areas of electrical engineering and computer science to create impactful solutions.
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The world of healthcare is changing fast and Commonwealth Radiology Associates is the “tip of the spear” when talking about advancements in Diagnostic Modalities, Image-Guided Intervention, AI, Machine Learning, and Health Blockchain Technology.
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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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We're looking for candidates who are passionate about exploring cutting-edge literature and technologies in machine learning, analytics, and data engineering to enhance our transactional systems excellence.
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Collaborate with other researchers and experts to develop machine-learning methods for problems in computational biology. Ph. D. degree in Computer Science, Machine Learning or a related field.
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As a Machine Learning Engineer, you will play a critical role in the development, deployment, and optimization of machine learning models with a strong emphasis on large language models (LLMs) and MLOps.
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machine learning source next jobs Company: Careerbuilder in Boston, MA
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Building a candidate pipeline through a great internship program for local college students and recent graduates at local universities is a great and cost-effective way to attract and retain top talent. By offering meaningful and impactful work experiences, regular feedback, coaching, and mentorship, you can create a positive internship experience that will make your organization a sought-after destination for future employees. This not only benefits the organization in the short-term but also in the long-term, as you'll have a pool of well-trained and experienced candidates who may be interested in full-time employment once they graduate. Furthermore, building relationships with local universities and college students can increase brand awareness and build a positive reputation for your organization in the local community.