Python programozó állások, munkák oktatás, tudomány, sport területen

• implementing and testing network theory and statistical algorithms
• participating in the documentation of research and development grant applications
• scientific literature search and processing
• communicating with research partners
• working according to ISO 9001 standards

•Nemzetközi belső AI os rendezvény szervezésének támogatása: információk gyűjtése, háttérkutatás, marketinganyagok tervezése, adminisztratív feladatok. •Kommunikációs anyagok összeállítása, rövid összefoglalók készítése, dokumentumok rendszerezése. •Oktatási anyagok előkészítésének támogatása:...

Egészségügyi adatbázisok, ellátáshoz kapcsolódó események, adatsorok feldolgozása. statisztikai értékelése, elemzések, kimutatások készítése és prezentálása;...

Conducting mathematical research in one of the above-mentioned subfields. Developing software packages to support the research project. Publishing research results and presenting them at conferences Contributing to teaching activities and, if required, supervising student assistants. ...

• Participation in the execution and organization of research projects
• Guided, but also independent execution of experimental research work in the aforementioned subject area, from programming experimental setups, data acquisition, and data analysis, to the dissemination of the results

• Ensuring the sustainability of community ESM codes, and enabling the adop­tion of modern HPC systems
• Enabling and improving high-performance computing capabilities of ESM codes, including performance optimization

Design, implementation, and maintenance of workflows for data processing, instrument control, as well as data transfer and storage for continuous atmospheric monitoring devices....

• design, construction and commissioning of a new Penning trap mass spectrometer,
• the application of state-of-the-art cryogenic detectors for the detection of individual particles in the traps and in the beam line,

• Become familiar with our previously developed neural network superstructure for learning iterative algorithms
• Extend the superstructure to tackle AC-PF problems of different complexities and assess its convergence in inference
• Investigate scaling and performance bottlenecks

• Automotive kijelzők optikai tervezése
• Innovatív megoldások keresése és ezek megvalósíthatóságának vizsgálata
• A kijelzők komponenseinek optikai szimulációja és optimalizálása, optikai specifikációk meghatározása
• Kísérleti kijelzők valamint prototípusok tervezése és építése

• 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

Develop and use innovative optimisation and decision analysis methods to model and assess energy transition strategies under consideration of economic, environmental, technical and social criteria...

• Development and implementation of numerical models for simulating microbial transport in porous media
• Modelling hydrogen conversion by subsurface microorganisms using suitable bio-chemical reaction kinetics models

- 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...

• Develop and apply frequency comb spectroscopy setups and utilize the existing CARS and QCLAS setups
• Apply the laser diagnostics to measure molecular species in atmospheric pressure plasmas related to plasma catalysis, such as COx, NOx, H2O2.

Develop and apply THz absorption spectroscopy and cavity-enhanced spectroscopy setups to measure atomic (O, Al) and molecular species (NO) and apply the existing E-FISH setup to measure electric fields in atmospheric pressure plasmas related to plasma catalysis...

• Drive pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Expand the horizon of what is possible by bringing together rich semantic context with large scale business data

• 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

• 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

to generate and harmonize user-friendly, standardized data analysis pipelines for a variety of computational tasks, including, but not limited to, mutation calling, bulk and single-cell RNA-seq analysis, ChIP-seq / Cut&Run analysis, CRISPR screen analysis, and DNA barcoding analysis,...