Job Description Summary In this role, you will understand complex and critical business problems, formulates integrated analytical approach to mine data sources, employ statistical methodsand machine learning algorithms to contribute solving unmet medical needs in neuroscience, discover actionable insights and automate process for reducing effort and time for repeated use. Moreover, you will manage the implementation and adherence … Good understanding of clinical study design principles and basic familiarity working with clinical data in a clinical trial (GxP) setting. Strong knowledge and understanding of (multivariate implementations of) statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modelling, longitudinal modelling, Bayesianmethods, variable selection methods (e.g., lasso, elastic net … random forest), design of clinical trials. Familiarity with statistical and analytical methods for high dimensional data (e.g. imaging, digital, genetics or -omics data). Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling. Excellent interpersonal and communication skills (verbal and writing) Ability to develop and deliver clear and concise presentations for More ❯
in the AI Lab. Responsibilities Develop new ML models and AI techniques Lead on research projects within a global team Review relevant AI/ML literature to identify emerging methods, technologies, and best practices. Explore new data sources and discover techniques for best leveraging data Minimum Qualifications A Master's or PhD in a field related to AI/… disciplines Strong background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, metrics, and benchmarks, and deploying production-ready solutions) Familiarity in statistical methods for Machine Learning (e.g. Bayesianmethods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with PyTorch, PyTorch Lightning, or similar frameworks Strong More ❯
analysis, gained through either an advanced quantitative degree or equivalent industry experience. Solid experience in some of the following areas: Causal inference, Marketing Mix Modeling, Multi Touch Attribution, Bayesian modeling, time series forecasting, experimentation. Hands on experience with cloud platforms (e.g., AWS, Azure, GCP)and MLOps tools for deploying and maintaining production ready, user facing solutions. Ability More ❯
mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new algorithms when an More ❯
mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new algorithms when an More ❯
Birmingham, West Midlands, United Kingdom Hybrid / WFH Options
Anson Mccade
frameworks (TensorFlow, PyTorch, or Caffe). Strong mathematical and statistical skills. Broad knowledge of core data science techniques, such as: Supervised/unsupervised machine learning Cross-validation andBayesian inference Time-series analysis and NLP SQL database querying and APIs for models Ability to innovate and develop new algorithms where needed. Leadership mindset - fostering technical growth, supporting More ❯
Central London, London, United Kingdom Hybrid / WFH Options
Singular Recruitment
libraries like mplsoccer . Advanced MLOps & Modelling: Deeper experience with the Vertex AI lifecycle (especially Pipelines ) and advanced modellingtechniques relevant to football (player valuation, tactical analysis). BayesianModelling: Experience with probabilistic programming (e.g., PyMC). Stakeholder Management: Proven success working directly with business stakeholders to define and deliver impactful solutions. What They Offer Work that More ❯
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 ❯
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, Bayesianmodelling, 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, andBayesian 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 ❯
relevant experience in statistics, mathematics, computer science, or equivalent experience with experience in research Proven experience applying machine learning techniques to solve business problems Proven experience in translating technical methods to non-technical stakeholders Strong programming experience in python (R, Python, C++ optional) and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf …/keras, langchain) Experience with version control (GitHub) ML experience with causality, Bayesianstatistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate models, transformers, Knowledge Graphs, Agents, Graph NNs, Deep Learning, computer vision Ability to write production code and object-oriented programming More ❯
in developing new machine learning for research, which involves AI4Science and for health, sequential decision making and experimental design under uncertainty, and collaborative AI. Machine learning keywords include Bayesian inference, distribution shifts, generative modelling, human-in-the-loop learning, privacy-preserving learning, reinforcement learning, inverse reinforcement learning, computational rationality and user modelling, and simulation-based inference. The 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 methodsand 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 methodsand 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 modellingmethods 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 ❯
