Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
with cloud-based computing platforms (AWS, Azure, Google Cloud) and high-performance computing (HPC) environments. Understanding of data privacy, security, and ethical considerations in handling clinical
-
biology approaches. Experience with HPC or cloud computing environments for large datasets. Equipment Utilized Physical Demands and Work Environment Overview Statement Posting Details Special Instructions
-
of the molecular ISM of galaxies, with a focus on galaxy centres. In particular, this project aims to measure the spatially resolved properties of giant molecular clouds and/or weigh the supermassive black holes
-
detection. Familiarity with real-time applications of AI/ML in embedded or IoT devices. Knowledge of cloud-based computing platforms for data processing (e.g., AWS, Google Cloud). Understanding of BMS
-
of the molecular ISM of galaxies, with a focus on galaxy centres. In particular, this project aims to measure the spatially resolved properties of giant molecular clouds and/or weigh the supermassive black holes
-
Deadline 29 Sep 2026 - 02:58 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
-
Deadline 13 Oct 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Dec 2025 Is the job funded through the EU Research Framework Programme? Not funded
-
technologies, including big data analytics, artificial intelligence (AI), remote data transfer, and cloud computing to help solve complex agricultural problems. -The candidate will work on the synthesis
-
Postdoc Impact of Computational Infrastructures on Public Institutions and Administration of Justice
”. Different scholars have located the power of clouds in market devices like intellectual monopolies (Rikap) or assetization (Birch), or in infrastructural aspects like computing arrangements for scale (Narayan
-
Sciences or related field. 2. Experience analyzing genomic, transcriptomic, proteomic or metabolomic data. 3. Experience with R. 4. Computer skills, including cloud computing. 5. Statistical skills