The Senior Statistical Programmer is responsible for providing hands-on support and technical guidance on clinical study teams. The development of study and ad hoc output, including, but not limited to: ADaM datasets, tables, figures, and listings output
Our client is headquartered in Switzerland – a biotech-hub of Europe – is a high-potential biopharmaceutical company, specialized in the discovery, development and commercialization of innovative small molecules, with the aim of transforming the horizon of
Our client, a high‑potential biopharmaceutical company headquartered in Switzerland, is looking for a Trial Data Manager for an initial 24‑month contract based in the Basel area. Trial Data Manager leads Data Management activities for assigned trials
Our client is headquartered in Switzerland – a biotech-hub of Europe – is a high-potential biopharmaceutical company, specialized in the discovery, development and commercialization of innovative small molecules, with the aim of transforming the horizon of
Job Description You will contribute to statistical activities related to global clinical trials and work closely with international teams of statisticians, programmers and data managers, including the role of biostatistics project lead. In this role, you will:
Project background Our research fellowship supported by EUMETSAT aims to integrate geostationary satellite observations into a next‑generation regional machine‑learning weather prediction system. The project builds on an existing graph‑based regional forecasting model at MeteoSwiss and is embedded
Project background Our research fellowship supported by EUMETSAT aims to integrate geostationary satellite observations into a next‑generation regional machine‑learning weather prediction system. The project builds on an existing graph‑based regional forecasting model at MeteoSwiss and is embedded
Machine Learning Scientist (AI-based Weather Forecasting) Recent advances in AI-based weather prediction have demonstrated remarkable skill and computational efficiency. However, most current machine-learning weather prediction (MLWP) systems rely primarily on NWP analyses for initialization and only