Data science állások Németországban (oktatás, tudomány, sport)

• A dynamic and interdisciplinary research environment
• Hands-on experience with EEG and fNIRS data acquisition and lab equipment
• Exposure to state-of-the-art methods in neural signal processing and data curation

Empower Founders: Support committed founding teams in turning validated ideas into early ventures. Strengthen their entrepreneurial judgement, execution capability, and founder mindset...

Inspire Founders: Empower students and researchers to turn bold ideas into ventures. Build their skills, mindset, and confidence to create and grow startups that matter...

• Develop cutting-edge optical smart instruments and medical imaging devices, utilizing multiple optical sensing modalities with a focus on medical robotics applications
• Test concepts, core functionalities, and analyze data generated by optical sensing-based hardware and software

• to develop automated workflows for descriptor-based microstructure reconstruction
• to identify material parameters for crystal plasticity simulations from experimental data through inverse analysis

Support students with regular queries concerning the requirements, structure, schedule, and enrolment procedure of curricular activities (courses, master's thesis, internships, skills workshops). Support is to be provided in person, via email, and via videocall ....

• Researching trends and innovative methods for transformation, AI and global learning & development
• Supporting the identification and documentation of concrete AI use cases, agents, and adoption opportunities in learning, leadership, and HR contexts

• Research on Atmospheric Microphysics in the AMP Department
• Strategic management and coordination of CAIS-ECAC within the framework of ACTRIS--ERIC
• Ensuring and monitoring scientific and qualitative standards for aerosol characterization

• planning, management and organization of epidemiologic research projects in the area of molecular and genetic epidemiology (with emphasis on omics technologies)
• development of data analysis plans
• data analysis of complex data from phenotyping, genotyping, sequencing and other omics sources