1 to 25 of 35 Neural Network Jobs in the UK

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 »

the following technical fields: Telecommunications, Computer Systems or other similar subject , with knowledge of one or more of the following: the air interface, core network, MIMO, small cell arrangements and network slicing in LTE and 5G, Wi-Fi network protocols and operation, cryptography or encryption, network security, quantum computing, computational physics, neural networks, virtualised and cloud computing, fault-tolerant computing, hardware design or database technologies. Working Location: This role will be carried out in-line with IPO Hybrid working arrangements where staff are currently expected to attend the office 1 day per week … be found via theCivil Service Pension Scheme Eligibility for special and office-wide bonus payments. The opportunity to form part of our many inclusive network groups, find out by looking atDisability Jobs,BME JobsandLGBT Jobs A variety of support functions including our excellent Staff Counselling Service which is a more »

/NLP/NATURAL LANGUAGE PROCESSING/DEEP LEARNING/DATA SCIENCE/LSTM/LONG SHORT TERM MEMORY/CNN/COGNETIVE NEURAL NETWORKS/CLOUD INFRASTRUCTURE/ARTIFICIAL INTELLIGENCE/INNOVATION/SECURITY CLEARANCE/DV CLEARED/SC CLEARED/SC CLEARANCE/SECURITY CLEARANCE 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 »

AI/Python/Data scientist/Machine Learning Engineer/Neural Networks/Deep Learning/LLMs Role: Lead Data Scientist Location: Remote - Occasional Meetings in London (Client) Company: AI Analytics Start-Up Salary: up to £130,000 Bonus Projects: Neural Networks, NLP, Machine Learning … with engineering team to bring analytical prototypes to production Generate actionable insights for business improvements Lead a small team of data scientist on Neural Networks LLMs (CNN & RNN), ML, & NLP NLP/AI/ML/Spark/Python/Data scientist/Machine Learning Engineer/OCR …/Deep Learning Requirements Bachelor's degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.) Experience with applied Neural Networks (CNN & RNN), LLMs Deep understanding of predictive modelling, machine-learning, clustering and classification techniques, NLP and algorithms Fluency in a programming language (Python, C more »

academic publications Excellent written and verbal communication skills The following skills are optional but desirable: Experience with Graph based algorithms such as Graph Neural Networks Working with knowledge graphs and graph databases Experience in a healthcare related field such as cell simulation, bio-informatics or genomics Achieve together more »

whilst supporting our employees. We are currently looking for a researcher in our Computing Research Group, working on exploring how the use Graph Neural Networks for healthcare related applications. We have a strong preference for the development of AI techniques that can be applied in the real … world and that directly contribute to social good. Your role will involve: The development of new state-of-the-art Graph Neural Network techniques to be applied to large scale data coming from healthcare applications Implementation of these techniques into proof-of-concept code and demonstrations that 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 »

with numerous publications at prestigious conferences. As a Research Engineer, you'll collaborate globally to tackle complex deep learning challenges, focusing on graph neural networks and pioneering new foundation models in healthcare. The Impact Your research will directly contribute to real-world applications with a profound social impact more »

particularly the command line interface. - Demonstrable experience in common AI/ML frameworks such as PyTorch, TensorFlow, OpenNN. - Knowledgeable in different types of neural networks and other ML techniques, including Gaussian Processes, confidence measures, clustering techniques, and application of neural networking techniques. Desirable Requirements: - Ability to 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 »

/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 »

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 »

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 »

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 »

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 »

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 »

engineering role, with exposure to: Implementing python libraries using OOP principles Experience applying DL or NN model architectures to geometric data (e.g., graph neural networks) Extensive experience with numerical and DL libraries (e.g., JAX and PyTorch) Using distributed computing frameworks (e.g., Ray) Docker for development and deployment Experience more »

advanced analytics or machine learning algorithms. An understanding of data science and machine learning concepts and algorithms such as clustering, regression, classification, forecasting, neural networks, hyperparameter tuning, NLP, and utilising LLMs. An understanding of the importance of effective communication with clients and experience of relaying complex technical concepts more »

using techniques such as Multi-Touch Attribution, Marketing Mix Modelling or similar would be highly desirable Knowledge of machine learning techniques such as Neural Nets, Random Forest or XgBoost and working with LLMs and associated techniques would be beneficial You are highly driven, dedicated, and have a keen more »

using techniques such as Multi-Touch Attribution, Marketing Mix Modelling or similar would be highly desirable Knowledge of machine learning techniques such as Neural Nets, Random Forest or XgBoost and working with LLMs and associated techniques would be beneficial You are highly driven, dedicated, and have a keen more »

market data, driving business strategy and the design of our quantitative market making platform Use advanced statistical analysis and quantitative techniques such as neural networks to build models that drive market making and risk management decisions in real time Be in the platform software development across a range more »

to solve real world financial problems Build/run in-house developed and third party ML models in production Deep learning research (Graph Neural Networks) Natural language processing (Semantic search, Generative LLMs) Datapoint extraction Develop novel methods to facilitate financial research from unstructured data. We are a research more »