Machine learning állások Németországban (kutató)

- development and parameterization of machine learning interatomic potentials - implementation of new algorithms in scientific software packages - generation of training data using electronic structure calculations, atomistic simulations - presentation of scientific results at conferences and in...

• Apply the frequency comb spectroscopy diagnostics to measure molecular species in low pressure plasmas related to industrial processes
• Develop and apply machine learning algorithms for data analysis and data-driven physics-constrained correlation mining

• Support postdoctoral researchers in conducting numerical simulations related to collaborative learning in wireless networks.
• Assist postdoctoral researchers with hardware demonstrations focused on collaboration and coordination among small radio devices.

• Research on learned components for streaming data systems, such as
• learned cost, latency, and throughput models for continuous and multimodal queries,
• learning-based scheduling, parallelism, and resource allocation for streaming operators, and

• Development of computational linguistic methods for the recognition and interpretation of (multimodal) metaphors
• Exploring the use of deep learning and LLMs for metaphor analysis
• Creation of annotated corpora and datasets
• Collaboration in an interdisciplinary team

• 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

· RESEARCH AND DEVELOPMENT: o Design novel orchestration architectures and algorithms for dynamic service placement, migration, and scaling across the cloud-edge continuum. o Devise and evaluate learning-based methods and control-theoretic approaches to balance latency, reliability, energy...

· RESEARCH AND DEVELOPMENT: o Design and evaluate distributed learning algorithms that operate across heterogeneous nodes, exploring model splitting, collaborative inference, and adaptive training strategies. o Investigate privacy-preserving and energy-efficient learning mechanisms and study the...

As postdoctoral researcher in Area I, you will contribute to a research project that focuses on the role of the solvent in charge or electron transfer processes. RESOLV aims to unravel the solvent impact on non-equilibrium charge and electron transfer processes at electrified interfaces, molecular...

• Develop methods and workflows to construct robust co-regulation networks from large single-cell and spatial transcriptomics datasets
• Integrate ontologies and metadata (e.g., tissue, cell type, developmental stage, treatment) to build tissue- and context-specific co-regulation networks

As postdoctoral researcher in Area II, you will contribute to RESOLV's aim to develop overarching guidelines for solvent selection and design to maximize yield and selectivity while minimizing the environmental footprint of chemical processes. Therefore, RESOLV integrates lab automation and...

• Develop and adapt bioinformatics approaches for the analysis of human genomic and epigenomic data sets
• Design and implement analysis workflows for the analysis of long-read whole-genome sequencing and targeted short-read sequencing (hybridization capture, MeDIP-seq) data