multi-modal datasets to derive quantitative biological insights to support their targeting to patient populations. You will develop efficient platforms to automate complex data analysis tasks, implement cutting-edge predictive approaches, and data visualization/modelling tools to promote efficiency of data-driven decision-making. You may also contribute … to presentations and publications of findings both internally and externally. EXAMPLE RESPONSIBILITIES: Design and implement pipelines for the analysis of antibody repertoire sequencing and use advanced methods to predict antibody function. Implement advanced statistical approaches for the analysis of large omics data sets and cross-modality data integration … and analysing both in house and publicly available disease derived data sets, specifically bulk and single-cell transcriptomics and proteomics. Designs and executes data analysis plans, communicates findings, and recommends follow-up actions in multiple settings, including one-to-ones, seminars, group, and project meetings. Participates in development of more »
integrity come together to advance the state of clinical development. Who Are You? An experienced Principal Biostatistician with a passion for clinical development and analysis, adept at utilizing advanced statistical methods, you will lead one Phase I-IV clinical studies across your region. You are excited and enthusiastic, motivate … Job Responsibilities: • Demonstrated experience in project leadership: project planning, interaction with different stakeholders, scientific supervision of statisticians. • Scientific leader: excellent knowledge and experience in survivalanalysis, and linear and generalized linear models. • Capacity to interface effectively with clinicians and statistical programmers. • Capacity to work independently. • Capacity to quickly … and apply it to clinical data. • Knowledge and practice of CDISC SDTM and ADaM data standards. • Ability to work in compliance with the company Analysis and Reporting SOPs and project data standards. • Able to re-in force the compliance. • Fast learner, team-oriented, able to work independently. • Knowledge of more »
of study design, protocol development, database design, data handling, trial management and statistical analysis. The majority of the time will be spent on the analysis of research data, ensuring that the appropriate statistical techniques are used, and presenting and explaining the results to users in a clear, comprehensible manner. … MS Office products Desirable Experience of presenting complex statistical information so that it is understandable to users without statistical knowledge. Experience of carrying out survivalanalysis and the application of other relevant statistical techniques. Experience in manipulating complex databases Experience in contributing to the statistical design of clinical … Strong analytical and problem solving skills, including the ability to select an appropriate methodology when analysing data Working knowledge of Stata (or similar statistical analysis packages) Computing and database skills Statistical analysis skills Report writing and written presentation skills Desirable Advanced Excel skills Knowledge of the disease process more »
s objectives by designing, implementing and deploying tools and solutions for a broad range of business objectives, such as asset pricing, demand forecasting, sentiment analysis, and other machine-learning techniques for pattern recognition and statistical modeling. You may also participate in due diligence analyses of future investments, or evaluate … reports to ensure data quality and business value. Clean, structure and normalize data to eliminate redundant or unnecessary information to enable robust and sound analysis Participate in the development of both back-end data pipelines and front-end applications Generate analytical reports to track adherence of client processes to … Mathematics, Engineering, Statistics, Computer Science or Physics. Advanced degree preferred but not required. Knowledge of Linear Algebra, Probability Theory, Statistics and Optimization, including regression analysis, parameter estimation, factors selection, PCA, hypothesis testing, time series, queuing theory, survivalanalysis, clustering, linear programming. Experience with machine learning methods, such more »
