26 to 45 of 45 Permanent Bayesian Methods Jobs

junior team members, leading research projects, and guiding collaborative efforts is a plus. Knowledge of the following machine learning domains is a plus. Generative models leveraging diffusion or Bayesian Flow Networks. Large-scale distributed machine learning training. Knowledge, experience or interest in the following biological domains is a plus. Drug discovery and protein engineering. Understanding of protein More ❯

attributes Track record shipping ML products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Visualization, data skills, SQL, matplotlib, etc. Benefits We are a well treated bunch, with awesome benefits! If there's something important More ❯

Several years of data science expertise, ideally within the supply chain domain A background in consulting and/or working within the cpg/retail industries Knowledge of Bayesian statistics, but broader ML experience, e.g. time series modeling and forecasting will be considered Strong communication skills, with the ability to distil and translate complex concepts into simple More ❯

skills Track record shipping ML products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background We are a well treated bunch, with awesome benefits! If there's something important to you that's not on this More ❯

experience within predictive modelling, machine learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects models, time series forecasting etc Strong programming ability, preferably in Python SQL and relational databases The company offer some great benefits including a bonus More ❯

experience within predictive modelling, machine learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects models, time series forecasting etc Strong programming ability, preferably in Python SQL and relational databases The company offer some great benefits including a bonus More ❯

deals. Strong hands-on skills in Excel and PowerPoint, including financial modeling and executive presentations. Solid understanding of statistical modeling techniques such as Linear Regression, Logistic Regression, and Bayesian methods. Excellent communication skills-both written and verbal-with the ability to clearly present complex concepts to non-technical stakeholders. Leadership presence with the ability to inspire teams More ❯

LeadingpharmaceuticalclientnowrequiresaSeniorDataScientisttodrivemarketingeffectivenessviamarketingmixmodellingandothermodels. Thisrolewilloverseedatacollection,extraction,manipulation,analysisandvalidationensuringdataisreadyformodelling. YouwillworkcloselywiththeDataScienceteamtobuildbasemodelsaccordingtoprojectspecificationsandensuretherobustnessandvalidityofthosemodels. Requirements: Strongexperiencedevelopingandimplementingmarketingmixmodels. ExpertinPythonandpreviousexperiencewithRprogrammingandideallywithMMMmodels. StrongexperiencewithPymcisessential. ExperiencewithRegressionbasedmodelsinanMMMcontext. Strongunderstandingofstatisticalmodelling/MachineLearningtechniques. ExperiencewithprobabilisticprogrammingandBayesianmethods Goodworkingknowledgeofcloud-baseddatascienceframeworks. Thisisa6monthcontractpositionwhichprovidesadailyrateof£688(InsideIR35). Intermsofworkingstructure,thisroleishybridwithonedayperweekintheirLondonofficeandtherestremote. More ❯

Strong coding skills in Python, with deep familiarity across ML and data libraries (pandas, numpy, scipy, scikit-learn, tensorflow, pytorch). A broad understanding of machine learning and statistical methods, including NLP, deep learning, Bayesian inference, time-series forecasting, and recommendation systems. Hands-on experience with cloud platforms such as AWS, GCP, or Azure, and exposure More ❯

Strong coding skills in Python, with deep familiarity across ML and data libraries (pandas, numpy, scipy, scikit-learn, tensorflow, pytorch). A broad understanding of machine learning and statistical methods, including NLP, deep learning, Bayesian inference, time-series forecasting, and recommendation systems. Hands-on experience with cloud platforms such as AWS, GCP, or Azure, and exposure More ❯

science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science methods (e.g. ML, NLP, Bayesian inference, APIs, SQL) Experience leading data science teams and managing project timelines Excellent communication and stakeholder engagement skills SC clearance and British More ❯

BigQuery for data modelling and warehousing Some examples of our data science work can be found in our engineering blog: Image catergorisation Moving to a A(/B) Bayesian World Scoring adverts quickly but fairly Life Cycle of Our Package Uplift Model What … We're Looking For Experience delivering data-science solutions in a commercial or research (e.g. PhD) environment A strong understanding of Data Science techniques, including ML algorithms and statistical methods Proficient in building ML pipelines with Python An enthusiasm for engaging with non-technical stakeholders and establishing scientific rigour in teams Experience collaborating on Data Science projects and working More ❯

maintenance. The ideal candidate will be a good communicator and have a growth mindset with an enthusiasm for scientific discovery and strong interest in applying a combination of AI methods and mathematical models toward understanding mechanistic aspects of cellular processes with all experimental labs at Altos Labs. The ideal candidate is particularly interested in multi-scale (systems) biochemistry and … loop between experimental and theoretical work, at multiple scales, from molecules to cells, tissues and even whole organisms. Working at the interface between mathematical and computational models, and AI methods, with the aim of establishing design principles of rejuvenated cells. Collaborating with both experimental and computational scientists across Altos. Influence best practices in areas such as Bayesian … Biology, Computational Biology, Computer Science, or closely related field with strong emphasis in biological modeling. Relevant industry and/or academic experience. Expertise and a track record of using methods from artificial intelligence for biological design. Record of applications of dynamical systems to problems of synthetic biology. Record of applications of data driven modeling methods and AI to More ❯

our services. Aid in business growth by engaging in client meetings, presentations, and proposals, highlighting the advantages and functionality of our technological offerings. Required Skills: Skilled in various modelling methods such as active learning, transfer learning, agent-based modelling, optimization, Bayesian inference, entity extraction/resolution, and spatio-temporal modelling. Proficient in developing models from fundamental More ❯

Qualifications Master's or PhD in Computer Science, Machine Learning, Data Science, or related field Good foundational understanding and subsequent practical application of ML techniques, preferably NLPs, LLMs, Bayesian Optimisation and MCMCs Strong proficiency in Python and ML frameworks and tools (e.g. PyTorch, TensorFlow, JAX, Hugging Face, vLLM, MCP, prompt engineering) Excellent communication skills and ability to … control tools (i.e. git, GitHub etc.) Experience with data scrapping (e.g. Beautiful Soup), extraction (e.g. LLMs) and cleaning. Knowledge with uncertainty quantification and probabilistic modelling approaches such as Bayesian optimisation Experience with cloud deployment pipelines (Docker, cloud platforms, AWS, CI/CD) Familiarity with sustainability or environmental data standards and frameworks What We Offer Opportunity to make More ❯

Qualifications Master's or PhD in Computer Science, Machine Learning, Data Science, or related field Good foundational understanding and subsequent practical application of ML techniques, preferably NLPs, LLMs, Bayesian Optimisation and MCMCs Strong proficiency in Python and ML frameworks and tools (e.g. PyTorch, TensorFlow, JAX, Hugging Face, vLLM, MCP, prompt engineering) Excellent communication skills and ability to … control tools (i.e. git, GitHub etc.) Experience with data scrapping (e.g. Beautiful Soup), extraction (e.g. LLMs) and cleaning. Knowledge with uncertainty quantification and probabilistic modelling approaches such as Bayesian optimisation Experience with cloud deployment pipelines (Docker, cloud platforms, AWS, CI/CD) Familiarity with sustainability or environmental data standards and frameworks What We Offer Opportunity to make More ❯

AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We’re looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that’s reinventing how the world designs and … all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that’s fusing AI, science, and engineering to push the boundaries of what’s More ❯

AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We’re looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that’s reinventing how the world designs and … all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that’s fusing AI, science, and engineering to push the boundaries of what’s More ❯

Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that's reinventing how the world designs and … all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science, and engineering to push the boundaries of what's More ❯

Research Fellows and Postdocs in Probabilistic Machine Learning and Bayesian Inference Aug 11, 2021 Research Fellows and Postdocs in Probabilistic Machine Learning and Bayesian Inference I am looking for researchers to my new team in Manchester, UK, funded by the UKRI Turing AI World-Leading Researcher Fellowship programme "Human-AI Research Teams - Steering AI … in Experimental Design and Decision-Making". Closing date of call: September 6, 2021. The research is fundamental research in probabilistic modelling and Bayesian inference, applied to the exciting problems of how do we steer machine learning systems. Particularly challenging is to steer when we cannot (yet) precisely specify our goal, and ultimately we would like to … design and decisions. I am not expecting anyone to master all of these, though if you do, please apply immediately The team will have excellent opportunities of applying the methods to medicine, especially cancer research and remote medicine; experimental design in synthetic biology and drug design; and digital twins. We have top-notch collaborators in each, both in Academia More ❯