51 to 75 of 102 Neural Network Jobs in the UK

Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science More ❯

Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science More ❯

Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science More ❯

Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science More ❯

Required I'm working with a deep-tech start-up looking for an experienced AI Engineer to join their expanding team. This role focuses on developing Neural Network-based NLP and Computer Vision algorithms, working alongside institutional, academic, and commercial partners. The Role • Develop/refine AI models for NLP • Design new scientific methods & experimental protocols • Analyze … meetings Key Requirements • Active SC Clearance (or eligible for SC Clearance) • MSc/PhD in CS, Engineering, Maths or relevant field (or equivalent experience) • Expertise in Neural Network-based NLP & LLM • Strong Python skills • Collaborative, analytical, and problem-solving mindset Gen AI Engineer – Hybrid (Oxford 2 Days/Week) – £100,000+ – SC Clearance Required More ❯

algorithms relevant to the platform. Delivering high-quality, specification-compliant code. Utilizing tools like OpenCV, TensorFlow, and other computer vision libraries. Applying knowledge of machine learning algorithms and neural networks to enhance processing techniques. Producing high-quality design documentation that adheres to software standards for regulated industries. Demonstrating proficiency in computer vision, image processing, and deep learning methodologies. More ❯

multi-disciplinary team, with diverse trading strategies across spot FX, NDFs, and swaps. The ideal people for these roles have eFX modelling experience and practical experience with applying neural nets to time series modelling. People who lack eFX experience, but have several years of real-world experience applying neural nets to time series in any industry More ❯

Woven by Toyota, we are at the forefront of developing advanced Machine Learning solutions for autonomous driving. Our team tackles groundbreaking challenges in designing state-of-the-art neural networks, pioneering innovative end-to-end architectures, and advancing ML techniques in perception, prediction, and motion planning. We're passionate about pushing the boundaries of autonomous systems through deep More ❯

thinking in reasoning and planning. Lead applied research projects end-to-end: from ideation and literature review to prototyping and deployment. Write high-quality, robust code that integrates neural and symbolic components. Collaborate with a team of scientists and engineers, articulating complex ideas clearly to technical and non-technical audiences. Analyse and inspect large-scale datasets to support … neural training and symbolic extraction. What We're Looking For: Deep learning expertise with significant industry experience, and c. 2+ years applying it to language generation, including working with Large Language Models, neurosymbolic integration and knowledge representation. Experience with Python and common ML Frameworks like Pytorch, HF Transformers, Tensorflow, JAX. Track record working as an independent contributor capable … engineers, and non-technical stakeholders. Desirable: Use of Python libraries that encourage best practices such as pytest, pylint, black etc. Experience with symbolic reasoning engines and integration with neural networks. Strong technical writing skills as evidenced by relevant publications or blogs. Start-up experience. Git/Github Proficiency working with cloud platforms for deploying hybrid AI systems. Please More ❯

extraction and transfer between LLMs and symbolic systems. You'll design and implement neurosymbolic architectures that preserve the interpretability advantages of symbolic AI while incorporating the flexibility of neural networks. Beyond the neurosymbolic integration work, you'll contribute to broader innovation around our core platform. You'll explore emerging technologies and methodologies that could enhance Rainbird's capabilities … relentless passion for driving innovation within the AI landscape. Preferred Experience Candidates who stand out will also bring: Experience in creating integrated AI systems that blend symbolic and neural methodologies, pushing the boundaries of conventional AI applications. Exposure to graph-based reasoning and the construction and utilization of knowledge graphs, facilitating sophisticated data relationships and inferencing. A background More ❯

and Experience: Previous experience within general insurance pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science More ❯

trends and issues in motor or home pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering. Knowledge of the technical differences between different packages for some of these model types would be an advantage. Experience in statistical and data science programming languages More ❯

feature engineering, build training pipelines, and achieve acceptable performance. At Kumo, we are building a machine learning platform for data lakehouses, enabling data scientists to train powerful Graph Neural Net models directly on their relational data, with only a few lines of declarative syntax known as Predictive Query Language. The Kumo platform enables users to build models a More ❯

finale of the fellowship is Demo Day. Fellows have the opportunity to present their hard work to an audience of 100+ guests. The event is a great chance to network with hiring managers and influential individuals from a wide range of businesses from London, the UK and Europe. After completing the Faculty Fellowship, our alumni have gone on to … The ability to code or have programming experience, especially in Python. Some experience with theoretical concepts of statistical learning (e.g. hypothesis testing, Bayesian Inference, Regression, SVM, Random Forests, Neural Networks, Natural Language Processing, optimisation). Experience with some coding libraries frequently used in data science. The ability to communicate effectively. Experience composing and following a project plan/… where all the fellowship alumni discuss data science news, techniques, conferences and much more. Faculty provides career support to the graduated fellows - once you are part of our "professional network", we will be delighted to keep in touch and help you succeed in your data science career. What we can offer you: The Faculty team is diverse and distinctive More ❯

quality, and cost. The AI Software Engineer will develop proof of concepts (POCs), secure business approval, and implement AI solutions at scale globally. Key skills include proficiency in neural networks, programming, NLP, prompt engineering, and hands-on experience with AI tools and frameworks. Collaboration with cross-functional teams and a strong understanding of data ethics and AI bias … and attention to detail. Strong communication and collaboration skills. Excellent organizational and time management skills. Attentive listening skills. Additional skills that are desirable but not mandatory include: Understanding Neural Networks: Proficiency in neural networks, including architectures like Convolutional Neural Networks (CNNs) and Transformers, is essential. This includes knowledge of activation functions and backpropagation techniques. More ❯

Join us at the heart of the Kumo Graph Neural Network and Relational Deep Learning architecture, where you'll play a pivotal role in shaping and expanding its capabilities. You'll drive innovative designs that enhance our GNN backbone and integrate cutting-edge temporal learning strategies. Your work will bridge the gap between foundational models and GNNs More ❯

list of benefits, speak to our recruitment team. We are looking for: We are particularly interested in candidates with experience in ONE of the following: Neuromorphic Computing, Spiking Neural Networks and event-based event monitoring/sparse data. Or: Advanced statistics and experience operationalising academic research Security clearance: You must be able to gain and maintain the relevant More ❯

Master's degree in Computer Science, Cybersecurity, AI, or related field. 8+ years of experience in cybersecurity, with expertise in AI security . Deep understanding of machine learning, neural networks, and adversarial attacks . Proficiency in cryptographic techniques and secure AI model development . Strong experience with penetration testing, threat intelligence, and security auditing . Familiarity with frameworks More ❯

thinking in reasoning and planning. Lead applied research projects end-to-end: from ideation and literature review to prototyping and deployment. Write high-quality, robust code that integrates neural and symbolic components. Collaborate with a team of scientists and engineers, articulating complex ideas clearly to technical and non-technical audiences. Analyse and inspect large-scale datasets to support … neural training and symbolic extraction. What We're Looking For: Deep learning expertise with significant industry experience, and c. 2+ years applying it to language generation, including working with Large Language Models, neurosymbolic integration and knowledge representation. Demonstrable experience leading in an individual contributor capacity-setting technical direction, influencing others, and delivering high-impact work without direct management … engineers, and non-technical stakeholders. Desirable: Use of Python libraries that encourage best practices such as pytest, pylint, black etc. Experience with symbolic reasoning engines and integration with neural networks. Strong technical writing skills as evidenced by relevant publications or blogs. Start-up experience. Git/Github Proficiency working with cloud platforms for deploying hybrid AI systems. Please More ❯

within Personal Lines Pricing, ideally including team or project leadership Proficiency in predictive modelling techniques such as Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets, and Clustering Strong skills in R, Python, PySpark, SAS, or SQL Proven ability to interpret performance data and make commercial recommendations Experience with WTW’s Radar and Emblem More ❯

within Personal Lines Pricing, ideally including team or project leadership Proficiency in predictive modelling techniques such as Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets, and Clustering Strong skills in R, Python, PySpark, SAS, or SQL Proven ability to interpret performance data and make commercial recommendations Experience with WTW's Radar and Emblem More ❯

software Experience in SOME of the following predictive modelling techniques e.g.Logistic Regression, Log-Gamma GLMs, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Support Vector Machines and Neural Nets Experienced in the use of a programming language (e.g. R, Matlab, Python or Octave) Experience of using Emblem and Radar Highly numerate with excellent attention to detail Ability More ❯

implementation and operational expertise. 2+ years directly running a technology pre-sales engineering organization and leading cross functional teams. Domain knowledge of service assurance, performance monitoring, routing, optical, optics, network automation, automation tools, SDN, ROADM, DWDM, metro core, access, edge, and aggregation network. Strong awareness and understanding of TWAMP, RON, SDN, SRv6, BNG, MPLS-SR, VxLAN, EVPN and ECMP. … as well as technical messaging with marketing as the voice of the customer. Strong understanding of AI/ML concepts, techniques & infrastructure (learning models, LLM, GenAI, AGI, NLP, neural networks, deep learning, AI Frameworks, GPU and DPU). Strong knowledge of customer networks, their current challenges, ability to act as consultant and guide the customers - particularly Service Providers More ❯

our Quantitative Trading & Market Making desk by developing market making and quoting strategies across equity products, from cash to derivatives. Utilize advanced statistical analysis and techniques such as neural networks to build models that inform systematic trading and risk management decisions in real time. Implement frameworks for centralized risk management and construct optimal portfolios across asset classes using More ❯

Mathematics, Physics, Statistics, or Engineering. Demonstrated experience developing systematic cash equity/statistical arbitrage strategies. Experience with machine learning models and/or statistical learning models (e.g. LLMs, neural networks, Deep Learning models, etc.). Capacity to excel in a fast-paced environment. Strong coding skills in at least one of the following programming languages: Python, R, MATLAB More ❯