1 to 25 of 58 Neural Network Jobs in England

/graphics processing or computer vision (minimum of 36 months experience) Solid background in one or more of the following: (i) neural network architectures, evidenced (for example) by knowledge of how to formulate and test advanced loss functions in neural network design; (ii) design … and test of advanced convolutional, recurrent, transformer-based or other neural network architectures in a task-specific manner; (iii) some experience in training, validation and evaluation of deep neural network models on large datasets, evidenced by experience in using Python libraries like HDF5 or more »

/graphics processing or computer vision (minimum of 36 months experience) Solid background in one or more of the following: (i) neural network architectures, evidenced (for example) by knowledge of how to formulate and test advanced loss functions in neural network design; (ii) design … and test of advanced convolutional, recurrent, transformer-based or other neural network architectures in a task-specific manner; (iii) some experience in training, validation and evaluation of deep neural network models on large datasets, evidenced by experience in using Python libraries like HDF5 or more »

Performance Tools Engineer in Cambridge, UK About Neubla As pioneers of innovative neural computing, Neubla is transforming the future of computing by bringing the enormous potential of neural computing to the highest performance in most data-intensive applications. Neubla is made up of people with expertise … CPU. However, in AI accelerator domain, the performance model has often been taken lightly due to the regular computation patterns of neural network models. However neural network models are getting bigger and much more complex every month, and it became almost impossible to estimate more »

and various foundational LLM's for Retrieval Augmented Generation (RAG) architecture including opensource would be desirable. Experience with graph machine learning (i.e., graph neural networks, graph data science) and practical applications thereof. This is complimented by your experience working with Knowledge Graph, creating ontologies leveraging Neo4j, GraphDB and more »

testing, and regression. Skilled in employing advanced machine learning algorithms and statistical techniques like regression, simulation, scenario analysis, modelling, clustering, decision trees, and neural networks to address business challenges. Demonstrated track record of applying statistical modelling and machine learning in industrial settings. Experience mentoring junior team members If more »

testing, and regression. Skilled in employing advanced machine learning algorithms and statistical techniques like regression, simulation, scenario analysis, modelling, clustering, decision trees, and neural networks to address business challenges. Demonstrated track record of applying statistical modelling and machine learning in industrial settings. Experience mentoring junior team membersIf this more »

testing, and regression. Skilled in employing advanced machine learning algorithms and statistical techniques like regression, simulation, scenario analysis, modelling, clustering, decision trees, and neural networks to address business challenges. Demonstrated track record of applying statistical modelling and machine learning in industrial settings. Experience mentoring junior team members If more »

selection, PCA, hypothesis testing, time series, queuing theory, survival analysis, clustering, linear programming. Experience with machine learning methods, such as regularization, random forests, neural networks and deep learning. Ability to write algorithms and implement pipelines in Python. Knowledge of Scala, R, is a plus. Experienced in SQL. Familiarity more »

Corporation or Microsoft would be a bonus. Experience: Experience in applying Artificial Intelligence in practical systems Experience in Machine Learning, NLP, Deep Learning, Neural Networks and data processing libraries (Tensorflow, Sci-kit learn, Pandas, Scipy, Numpy at least three or more) Experience in Data mining, Data warehousing, ETL more »

techniques quickly is essential. Some Experience in running various methods like Regression, Random forest, k-NN, k-Means, boosted trees, SVM, Neural Network, text mining, NLP, statistical modelling, data mining, exploratory data analysis, statistics (hypothesis testing, descriptive statistics). Experience of manipulating large quantities of high-dimensional … diversity and has professional experience in working in different places, different industries and different geographies. Ability to form impactful and trusted partnerships across the network and ensure sustained, fruitful and meaningful collaboration with all relevant stakeholders. Your role at Mediprospects.ai is integral to helping the world meet new breakthroughs more »

stakeholders, so it s equally important that IT Project Managers understand how to manage stakeholder relationships. Experience in Machine Learning, NLP, Deep Learning, Neural Networks and data processing libraries (Tensorflow, Sci-kit learn, Pandas, Scipy, Numpy at least three or more) Experience in in management either at a more »

PowerPoint and presentation/communication skills Expertise in predictive modelling, including both parametric (e.g. logit/probit) and non-parametric (e.g. random forest, neural net) techniques as well as wider ML techniques like clustering/random forest (desirable) Tech Stack: SQL, Python, R, Tableau, Power BI, AWS Athena more »

management experience, with a knack for leading cross-functional teams and mentoring. - Advanced analytical skills, with experience in deep learning and knowledge of neural networks (TensorFlow, PyTorch). - Familiarity with cloud computing platforms (AWS, GCP, Azure) and MLOps practices, including tools like MLFlow, BentoML, and Evidently AI. - Awareness more »

well as a deep understanding of how to implement solutions using Retrieval Augmented Generation (RAG) architecture. Expertise in graph machine learning (i.e. graph neural networks, graph data science) and practical applications thereof. This is complimented by your experience working with Knowledge Graphs, ideally biological, and a familiarity with more »

ROLE: Your day-to-day responsibilities will include: Building, deploying and productionising segmentation, churn, and recommender system-based projects, alongside deep learning and neural networks to support core internal projects Part of a team of 7 reporting to the Head of Data Science Chance to upskill and mentor more »

and industry-leading computing tools to apply and build ML models from the ground up, utilizing new and established techniques and methods like neural networks, reinforcement learning, deep learning, and natural language processing. Remain connected to the broader research community, staying on top of the latest research and more »

applications and projects - Proven work experience as a Gas Processing AI Engineer or in a similar role - Strong knowledge of machine learning algorithms, neural networks, and deep learning frameworks (e.g., TensorFlow, PyTorch) - Strong knowledge of plant networks and infrastructure requirements to deploy and scale AI in gas plants more »

Role:Your day-to-day responsibilities will include:Building, deploying and productionising segmentation, churn, and recommender system-based projects, alongside deep learning and neural networks to support core clientsPart of a team of 12 reporting to the Head of Data ScienceChance to have 1 direct report within an more »

discipline e.g. engineering, mathematics, physics, statistics Experience of data science in finance, insurance or Ecommerce is an advantage but not required. Experience with neural networks and Tensor Flow, CatBoost, XGBoost, SKlearn, Pandas Our technology We are currently developing a new data platform in databricks that encompasses all our more »

web apps Experience with modern data tools, ideally Tableau, Jupyter Notebooks, Pandas and Python visualisation libraries Exposure to machine learning approaches such as neural networks, NLP, generative AI desirable Experience working at an investment management company Experience with manging Agile delivery, preferably Kanban and Scrum. Ability to communicate more »

Role: Your day-to-day responsibilities will include: Deploying and productionising core segmentation, churn, and recommender system-based projects, alongside deep learning and neural networks to support core clients Part of a team of 9 reporting to the Head of Data Science - working closely with a wider Engineering more »

Role: Your day-to-day responsibilities will include: Building, deploying and productionising segmentation, churn, and recommender system-based projects, alongside deep learning and neural networks to support core clients Part of a team of 12 reporting to the Head of Data Science Chance to have 1 direct report more »

Advanced degrees in fields such as engineering, mathematics, physics, or statistics. Background in data science within finance, insurance, or eCommerce sectors. Experience with neural networks and tools like TensorFlow, CatBoost, XGBoost, SKlearn, and Pandas. Benefits: Competitive salary. 25 days annual leave, plus additional company-specific days. 4-week more »

Engineer Strong foundation in Python Excellent knowledge of ML libraries and frameworks like TensorFlow, PyTorch, Keras and scikit-learn. Experience with neural network architectures, deep learning techniques, and building and training deep learning models. Creating and handling large datasets including pre-processing steps and familiarity with data more »

Strong Python skills and understanding of data science and machine learning concepts and algorithms such as clustering, regression, classification, forecasting/predictive analytics, neural networks, hyperparameter tuning, NLP, and utilising LLMs. - **Communication:** Strong ability to communicate complex technical concepts to diverse audiences effectively. - **Management:** Previous line management experience. more »