130 algorithm-development research jobs at Rutgers University in Ireland-University-Ranking-2024
Sort by
Refine Your Search
-
Experience developing software with Python, R, and/or Julia Experience with machine learning and AI algorithms and tooling (e.g. PyTorch) Experience with remote sensing and open-source GIS tools (e.g. Google
-
, etc. - ML-augmented numerical method development. - High-performance computing (HPC). - Quantum algorithm design. - Error correction or error mitigation. City
-
scientific independence, including opportunities to develop first-author publications and pursue independent funding to embark on an academic career in the area of nephrology. This position is ideally suited
-
/benefits/benefits-overview . Posting Summary RCSB Protein Data Bank is seeking a highly motivated database programmer with experience in database administration and domain experience in computer science
-
: Strong skills in developing biosignal processing algorithms and implementing machine learning models for data interpretation. Technical Oversight: Ability to monitor complex data collection processes and
-
learning and quantum information science. Candidates with experience in method development and high-performance computing are especially encouraged to apply. A Ph.D. in chemistry, physics, computer science
-
patients from public repositories (including dbGaP). Develop and apply machine learning algorithms to associate patterns in the data with cancer progression and therapeutic response in prostate cancer
-
Associate will conduct translational epilepsy research focused on the network mechanisms of ictogenesis in mesial temporal lobe epilepsy (MTLE). The researcher will develop and validate quantitative, event
-
include but is not limited to 1) developing, validating, improving and applying cell-based and other preclinical models to understand the functions of lipids, lipoproteins and related factors in influencing
-
include (but are not limited to) developing/applying new approaches to improve range shift projections under climate change, regionally modelling organism-environment interactions across species ranges