51 to 71 of 71 Neural Network Jobs

/Machine Learning Data Scientist into a highly visible front-office AI Lab environment. The team is focused on applying advanced ML, neural networks, and predictive modelling techniques to highly complex portfolio, equities, and client behaviour problems within a large-scale Prime business generating substantial annual revenues. … exceptionally fast paced Strong preference for candidates who have: built and deployed ML models in production strong Python/PyTorch capability neural network experience advanced statistical/mathematical foundations experience solving complex prediction or optimisation problems ability to lead technically while remaining hands-on The role sits ...

scalable. What you’ll do: Lead the development and refinement of novel machine learning architectures and algorithms harnessing our nonlinear dynamics. Building deeper network architectures that maximise efficiency and performance. Design, build and test models both on device and using in-house simulation framework. Collaborate closely with the wider … NeurIPS, ICML, ICLR, CVPR, or Nature/Science journals) Hardware Aware ML/Neuromorphic Computing: FPGAs, ASICs, analog computing chips, spiking neural network (hardware), edge AI Unconventional training algorithms Reservoir computing, self-constrastive learning, forward-forward learning, evolutionary algorithms, equilibrium propagation Physics informed neural networks ...

Estimation Deep Learning techniques : Detection, Classification, Tracking, Siamese Networks Inverse Problems/Computational Imaging : Sparse Coding, Compressive Sensing Machine Learning : Support Vector Machines, Neural Networks Domain Specific Signal Processing : Multi/Hyper-Spectral, RF, IR, SAR, STAP The primary development environments used within the department are Matlab/ ...

Your work will raise the bar for capability, reliability, and speed of iteration. Responsibilities Key objective is to develop and deploy robust deep neural networks for robotics, supported by object detection, segmentation, and scene understanding models. Build scalable pipelines for training, fine‐tuning, inference, and real-time optimization ...

access to large-scale, unique data Deep expertise in at least two of: LLMs and foundation models (pretraining, fine-tuning, distillation), physics-informed neural networks, or reinforcement learning Experience with agent frameworks, tool-use planning and workflow orchestration Systems-level fluency across data pipelines, training infrastructure and inference ...

wellbeing. This particular role is for an AI specialist who is familiar with a wide range of AI methods, ranging from deep neural networks, to language models and agentic systems. You should have experience of using Python, frameworks like Keras, Pytorch and platforms like Azure and AWS. ...

synthetic data generation, and scalable ML infrastructure to improve robotics capability and deployment speed. A key responsibility will be developing robust neural network architectures focused on object detection, segmentation, pose estimation, and scene understanding. The successful candidate will work on models that directly impact robotic perception ...

machine learning methods 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 DevOps and Azure ML, or other MLOps and ML Lifecycle technology stacks, such as AWS, Databricks, Google Cloud, etc. ...

helping design, train, and deploy perception systems — from image segmentation and object classification through to stereo camera pipelines and real-time deep neural inference. You will work closely with robotics, embedded, and systems engineers to bring cutting-edge vision intelligence into production agricultural environments What … Will Do: - Design and implement machine learning pipelines for image segmentation, object detection, and 3D scene reconstruction. - Train and optimise deep neural network models using frameworks such as PyTorch and TensorFlow. - Manage and curate training datasets, including developing data augmentation and annotation strategies. - Deploy machine learning models ...

imagery and computer vision , including remote sensing Reinforcement learning Natural language processing and large language models Knowledge graphs and graph‐based neural networks AI applied to RF, electronic warfare, radar, sonar, or acoustics Autonomy and intelligent systems Evidence of published research in relevant journals or conferences ...

cross-functional teams to identify challenges and implement innovative solutions tailored to the organization’s needs. Qualifications Strong expertise in Pattern Recognition and Neural Networks Proficiency in Computer Science and Software Development Experience in Natural Language Processing (NLP) techniques and applications Proven problem-solving and critical thinking skills ...

within data science Experience in insurance pricing and modelling Experience and detailed technical knowledge of GLMs/Elastic Nets, GBMs, GAMs, Random Forests, Neural Networks and clustering techniques Knowledge of statistics and distributions commonly used in insurance Experience in programming languages (e.g. Python, PySpark, R, SAS, SQL) Proficient ...

AlphaFold, protein embeddings, or molecular simulation outputs Knowledge of antibody developability, binding affinity prediction, or therapeutic optimisation workflows Experience with diffusion models, graph neural networks, or generative protein design approaches Publications in machine learning, protein modelling, computational biology, or AI for Science Why Join? Build frontier AI systems ...

experience. Comprehensive benefits package including bonus potential. Flexible hybrid working arrangements. Opportunity to work on highly advanced computing platforms and neural network technologies. Exposure to cutting-edge hardware and software development programmes. Long-term projects with genuine technical depth and complexity. Due to the nature ...

transforming research findings into functional business tools. Support the development and evaluation of ML models, including both standard machine learning and neural network-focused models, as requested by R&D teams. Develop standardised, reusable workflows that can be applied across different projects and scientific areas. Collaborate with ...

designing, building, and maintaining scalable data pipelines for structured and unstructured data Develop, train, and evaluate machine learning and deep learning models, including neural networks Work with Large Language Models (LLMs) for tasks such as text generation, summarization, and semantic analysis Contribute to Generative AI (GenAI) applications … learning concepts and algorithms Familiarity with frameworks such as TensorFlow (or PyTorch equivalent) Basic knowledge of Natural Language Processing (NLP) techniques Understanding of Neural Networks and deep learning fundamentals Exposure to Generative AI concepts and LLMs (e.g., prompt engineering, embeddings) Knowledge of working with APIs and data exchange ...

high-pace startup environment. Knowledgeable about physical engineering or related domains such as robotics or cognitive science. Experience working with PINNs (physics-informed neural networks) or graph neural networks for physics-based surrogate models. Experience owning or being involved longer-term in an open source project ...

ensure that our core lending capabilities remain at the forefront of the industry. Unlock the value in non-traditional datasets by building sophisticated neural networks (e.g. LSTMs, RNNs, or Transformers). You will find novel ways to transform raw, multi-modal inputs into powerful predictive features. Collaborate with … associates Mind Your Mind – signposting support and promoting positive mental wellbeing for all Women in Tech – promoting an inclusive environment in tech EmpowHER - network of female associates and allies focusing on developing future leaders, particularly for female talent in our industry Capital One is committed to diversity ...

ensure that our core lending capabilities remain at the forefront of the industry.Unlock the value in non-traditional datasets by building sophisticated neural networks (e.g. LSTMs, RNNs, or Transformers). You will find novel ways to transform raw, multi-modal inputs into powerful predictive features.Collaborate with business stakeholders … LGBTQ+ support for all associatesMind Your Mind – signposting support and promoting positive mental wellbeing for allWomen in Tech – promoting an inclusive environment in techEmpowHER - network of female associates and allies focusing on developing future leaders, particularly for female talent in our industryCapital One is committed to diversity ...

handling and curation, and mentoring the interdisciplinary team in machine-learning and data analysis methods. 4. Stay current with breakthroughs in machine learning, neural networks, NMR, and computational technologies, contributing to the design and execution of cutting-edge machine learning and NMR research projects. ROLE REQUIREMENTS … Words: Machine Learning Engineer/Data Processing/Model Building/NMR/Deep Learning/Computational Biophysics/Drug Discovery/Neural Networks/Scientific Software/Python/Nuclear Magnetic Resonance Hyper Recruitment Solutions Ltd (HRS) is an Equal Opportunities employer. We welcome applications from anyone ...

appropriate tests. Excellent communication skills with the ability to talk to non-technical and non-scientific stakeholders. Any exposure to training ML models (neural networks) would be desirable. This role would predominately be based at offices in Cambridge (although some flexibility for hybrid working would be possible when … have full rights to work in the UK without any restrictions. Keywords: Start-Up, Life Sciences/Biotech, Python, Platform Development, Machine Learning, Neural Networks, Data Science, Cambridge Another top job from ECM, the high-tech recruitment experts. Even if this job's not quite right, do contact ...