1 to 25 of 49 Remote Experimental Design Jobs in the UK

or completed Masters and/or PhD is preferred but not required Fluency in English (native or bilingual level) Detail-oriented Proficient in biology and inductive/deductive reasoning, experimental design, data interpretation, and systems-level thinking. Note: Payment is made via PayPal. We will never ask for any money from you. Job Types: Full-time, Part More ❯

or completed Masters and/or PhD is preferred but not required Fluency in English (native or bilingual level) Detail-oriented Proficient in biology and inductive/deductive reasoning, experimental design, data interpretation, and systems-level thinking. Note: Payment is made via PayPal. We will never ask for any money from you. Job Types: Full-time, Part More ❯

or completed Masters and/or PhD is preferred but not required Fluency in English (native or bilingual level) Detail-oriented Proficient in biology and inductive/deductive reasoning, experimental design, data interpretation, and systems-level thinking. Note: Payment is made via PayPal. We will never ask for any money from you. Job Types: Full-time, Part More ❯

or completed Masters and/or PhD is preferred but not required Fluency in English (native or bilingual level) Detail-oriented Proficient in biology and inductive/deductive reasoning, experimental design, data interpretation, and systems-level thinking. Note: Payment is made via PayPal. We will never ask for any money from you. #INDUKBIO Job Types: Full-time More ❯

at Pear Bio. Job Responsibilities Develop and implement machine learning and statistical models for target discovery, drug development and patient response prediction. Collaborate with wet-lab scientists to design experiments and analyze results to inform target and drug discovery efforts. Integrate and analyze multi-omic datasets (genomics, transcriptomics, proteomics), imaging data and clinical data to extract meaningful insights. … Build robust data pipelines for processing, integrating, and mining structured and unstructured biomedical data. Design and develop interactive dashboards and visualization tools to support data-driven decision-making. Work on single-cell resolution data from high-throughput imaging pipelines to identify biomarkers and therapeutic targets. Present findings in internal meetings and contribute to scientific publications and conferences. Stay More ❯

or completed Masters and/or PhD is preferred but not required. Fluency in English (native or bilingual level). Detail-oriented. Proficient in biology, inductive/deductive reasoning, experimental design, data interpretation, and systems-level thinking. Note: Payment is made via PayPal. We will never ask for any money from you. #J-18808-Ljbffr More ❯

at Pear Bio. Job Responsibilities Develop and implement machine learning and statistical models for target discovery, drug development and patient response prediction. Collaborate with wet-lab scientists to design experiments and analyze results to inform target and drug discovery efforts. Integrate and analyze multi-omic datasets (genomics, transcriptomics, proteomics), imaging data and clinical data to extract meaningful insights. … Build robust data pipelines for processing, integrating, and mining structured and unstructured biomedical data. Design and develop interactive dashboards and visualization tools to support data-driven decision-making. Work on single-cell resolution data from high-throughput imaging pipelines to identify biomarkers and therapeutic targets. Present findings in internal meetings and contribute to scientific publications and conferences. Stay More ❯

deliver new computational analysis methods to our customers Collaborate with external partners to test the technology in their use cases and drive the collaborative work towards scientific publication Design experiments to understand the utility of our technology in various aspects Provide feedback to internal product development teams (molecular biology and bioinformatics software) to drive optimisation of our assays … etc.) PhD or equivalent experience in a biological subject area, with a strong focus on informatics and data analysis Detailed understanding of methods used in genomic data science, including experimental design, QC, and common analysis methods such as variant calling, QTL mapping, GWAS/EWAS Enjoy working in a fast-moving, results-oriented business where delivery against More ❯

Location: Remote/Hybrid/USA-SF, USA-remote, UK-London, UK-remote Responsibilities: Translate predictive modeling problems and business constraints into robust Bayesian or probabilistic AI solutions. Design and implement reusable libraries of predictive features and probabilistic representations for diverse ML tasks. Build and optimize tools for scalable probabilistic inference under memory, latency, and compute constraints. Apply … modern AI use cases. Collaborate closely with product, engineering, and business teams to build end-to-end modeling solutions. Conduct deep-dive statistical and machine learning analyses, simulations, and experimental design. Stay current with emerging trends in generative modeling, causality, uncertainty quantification, and responsible AI. Requirements/Qualifications: Strong experience in Bayesian inference and probabilistic modeling : PGMs, HMMs, GPs More ❯

and interpret models. Shape the R&D strategy and modelling roadmap. Assist in acquiring vendor data and develop arguments. Provide expert mentorship for ongoing and new pricing activities. Design experiments and multivariate testing for AI evaluation. Assess machine learning solutions for feasibility and operationalize successful prototypes with Data Engineers. Use statistical techniques to optimise business performance. Develop and More ❯

and interpret models. Shape the R&D strategy and modelling roadmap. Assist in acquiring vendor data and develop arguments. Provide expert mentorship for ongoing and new pricing activities. Design experiments and multivariate testing for AI evaluation. Assess machine learning solutions for feasibility and operationalize successful prototypes with Data Engineers. Use statistical techniques to optimise business performance. Develop and More ❯

and interpret models. Shape the R&D strategy and modelling roadmap. Assist in acquiring vendor data and develop arguments. Provide expert mentorship for ongoing and new pricing activities. Design experiments and multivariate testing for AI evaluation. Assess machine learning solutions for feasibility and operationalize successful prototypes with Data Engineers. Use statistical techniques to optimise business performance. Develop and More ❯

deliver new computational analysis methods to our customers. Collaborate with external partners to test the technology in their use cases and drive the collaborative work towards scientific publication. Design experiments to understand the utility of our technology in various aspects. Provide feedback to internal product development teams (molecular biology and bioinformatics software) to drive optimisation of our assays … . PhD or commensurate experience in biological subject area, with a strong focus on informatics and data analysis. Detailed understanding of the methods used in genomic data science, including experimental design, QC, and common methods of secondary and tertiary analysis such as variant calling, QTL mapping, and GWAS/EWAS. Enjoy working as part of a fast More ❯

it’s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real … world problems Carrying out full data science workflows: from data acquisition and cleaning to modelling, validation, and deployment Applying statistical and AI techniques to generate actionable insights Contributing to experimental research, model prototyping, and A/B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable … unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: 💰 Competitive Salary & Bonus : £35,000 – £45,000 plus performance-based More ❯

it’s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real … world problems Carrying out full data science workflows: from data acquisition and cleaning to modelling, validation, and deployment Applying statistical and AI techniques to generate actionable insights Contributing to experimental research, model prototyping, and A/B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable … unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: 💰 Competitive Salary & Bonus : £35,000 – £45,000 plus performance-based More ❯

as we move towards our goal of dramatically accelerating and improving the process of designing and bringing new medicines to patients. We have built a world-leading drug design engine comprising foundational AI models that are capable of working across multiple therapeutic areas and drug modalities. The company is continually innovating on model architecture and developing cutting-edge … one or more critical problems in drug development. Identify and create novel ML approaches, model architecture, and training strategies, along with the required data to train. Analyse and tune experimental results to inform future experimental directions. Work within cross-functional ML Research, Chemistry, Engineering and Biology Teams, to direct research hypotheses and deliver outstanding research. Use your experience … ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas Expertise with detailed data quality control procedures and data visualisation Experience with experimental design and statistical analysis Demonstrated understanding of computational biology tools and methodologies and experience with the analysis of large -omics datasets Familiarity with a variety of assaying More ❯

completed Masters and/or PhD is preferred but not required. Fluency in English (native or bilingual level). Detail-oriented. Proficient in biology and inductive/deductive reasoning, experimental design, data interpretation, and systems-level thinking. Benefits This is a full-time or part-time REMOTE position. You’ll be able to choose which projects you More ❯

in-office work. Discover more about our company wide benefits and life at GSK on our webpage Life at GSK GSK In this role you will Lead the design, development, and deployment of advanced AI/ML models across the R&D domain (drug discovery, genomics, clinical trials, and more). Translate complex scientific and business problems into … and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face). Experience building and deploying models in cloud environments (e.g. Azure, GCP). Solid understanding of statistics, optimization, and experimental design. Preferred Qualifications & Skills: Please note the following skills are not necessary, just preferred, if you do not have them, please still apply: Prior experience in pharmaceutical R&D More ❯

between technical AI capabilities and practical business applications, using bespoke coding and modern low-code/no-code automation platforms in an ever changing marketing landscape. KEY RESPONSIBILITIES Design and build intelligent workflow automation solutions for media and marketing teams using AI-powered tools and frameworks Develop POCs that demonstrate how AI can streamline content creation, campaign management … applicable Create API integrations between marketing tools, CRM systems, and content management platforms using MCP or alternative protocols. Perform statistical analysis including A/B testing, causal inference, and experimental design to build the business case of POC's Work closely with data engineers, media consultants and clients to ensure seamless integration of your solution to create More ❯

scaffolding, prompting. Broad experience in empirical research methodologies, potentially in fields outside of machine learning, and statistical analysis (T-shaped: some deep knowledge, lots of shallow knowledge, in e.g. experimental design, A/B testing, Bayesian inference, model selection, hypothesis testing, significance testing). Deeply care about methodological and statistical rigor, balanced with pragmatism, and willingness to More ❯

that shape business strategy. If this interests you, please keep reading below for more information Responsibilities Design and analyse causal inference experiments using both randomized and quasi-experimental methods Develop conformal prediction models to quantify uncertainty in machine learning predictions Identify and account for confounding variables in observational studies Create and apply statistical frameworks to estimate causal … effects accurately Collaborate with product, engineering, and business teams to design rigorous experiments Present insights and methodologies in a clear and actionable way to stakeholders Translate complex data challenges into impactful, data-driven solutions Qualifications … Advanced degree (MS/PhD) in a quantitative field with strong statistical expertise 3+ years of hands-on experience applying statistical methods to real-world data Deep knowledge of experimental design and observational study techniques Strong understanding of conformal prediction theory and applications Proficient in Python or R, with experience in statistical and machine learning libraries Familiarity More ❯

leadership to align hardware, software, and platform groups. Represent the company in customer meetings, incorporating feedback into architectural decisions. Create high-level architecture specifications to guide engineering teams. Design experiments and analyses to address architectural questions using appropriate tools and methods. Communicate technical concepts effectively across diverse audiences. Key Requirements: Proven track record in smartphone/tablet SoC … Science, or related field; MS or PhD highly desired. Keywords: SoC Architecture/System-on-Chip/Mobile Computing/Platform Architecture/Hardware-Software Integration/Semiconductor Design/Technology Roadmap/IP Evaluation/Cross-Functional Leadership/Embedded Systems/High-Performance Computing/Energy Efficiency/Architecture Specification/Simulation and Modelling If you …/07/European-Tech-Recruit-Privacy-Notice-2024.pdf Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Engineering, Design, and Research Industries Semiconductor Manufacturing and Computers and Electronics Manufacturing Referrals increase your chances of interviewing at European Tech Recruit by 2x Chief AI System Software & Hardware Co-design More ❯

analytics that shape business strategy.If this interests you, please keep reading below for more information Responsibilities • Design and analyse causal inference experiments using both randomized and quasi-experimental methods• Develop conformal prediction models to quantify uncertainty in machine learning predictions• Identify and account for confounding variables in observational studies• Create and apply statistical frameworks to estimate causal … effects accurately• Collaborate with product, engineering, and business teams to design rigorous experiments• Present insights and methodologies in a clear and actionable way to stakeholders• Translate complex data challenges into impactful, data-driven solutions Qualifications … Advanced degree (MS/PhD) in a quantitative field with strong statistical expertise• 3+ years of hands-on experience applying statistical methods to real-world data• Deep knowledge of experimental design and observational study techniques• Strong understanding of conformal prediction theory and applications• Proficient in Python or R, with experience in statistical and machine learning libraries• Familiarity More ❯

maintain robust LTV (Lifetime Value) forecasting models to inform marketing spend and retention strategies. Build demand forecasting models to ensure demand planning aligns with acquisition and retention trends. Design, run, and analyse A/B tests and multivariate experiments across acquisition funnels, onboarding flows, and retention programs. Collaborate with cross-functional teams to translate business goals into data … industry best practices. What We're Looking For 5+ years of experience in data science, ideally in growth, marketing, or product-focused roles. Understanding of LTV modeling, forecasting, and experimental design. Comprehension of A/B testing methodologies Proficiency in Python for data analysis and modeling (e.g., pandas, scikit-learn, statsmodels). Strong SQL skills and experience working with More ❯

of improvements to processes implemented on our automation platforms. - Work with cross-functional teams (sample preparation & PCR optimization and integration, troubleshooting and failure analysis) to identify and prioritize design improvements based on data collated from customers, field service, technical support and/or research & development. - Design experiments to reproduce systemic issues, determine the root causes and … teams. - Knowledge of quality methods such as CAPA, cGMP, FMEA, ISO would be beneficial. - Experience with product development and/or life cycle management in a regulated environment (Design Controls according to European and U.S./FDA guidelines) would be a plus. - Knowledge of Solid Works (or other equivalent CAD package). - Willingness and availability to travel to … of improvements to processes implemented on our automation platforms. - Work with cross-functional teams (sample preparation & PCR optimization and integration, troubleshooting and failure analysis) to identify and prioritize design improvements based on data collated from customers, field service, technical support and/or research & development. - Design experiments to reproduce systemic issues, determine the root causes and More ❯