707 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" positions at Harvard University in United States
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
an individual with a PhD to conduct research in the area of biomedical informatics, multi-omic integratoin analytics and machine learning. In this role you will produce highly impactful biomedical informatics
-
potwashing/dish area, walls, floors and counters. Fills, empties, operates and performs regular maintenance on pot washing machine or manually washes pots as required. Monitors and records temperatures and
-
potwashing/dish area, walls, floors and counters. Fills, empties, operates and performs regular maintenance on pot washing machine or manually washes pots as required. Monitors and records temperatures and
-
with a desire to research and learn more about biomedical research, multi-omic integration analytics and machine learning. In this role you will produce highly impactful biomedical informatics research
-
customer service orientation. Strong computer skills (Word, Excel, PowerPoint, Outlook, and internet) and willingness/ability to learn and adapt to new software and technologies. Experience with or knowledge
-
Science Statistics / Biostatistics Applied Mathematics Data Science Demonstrated expertise in modern machine learning, including at least one of the following: Deep learning (e.g., transformers, sequence models
-
of public benefits, and generative AI-based tools. Leverage recent breakthroughs in machine learning and natural language processing to build, test, and deploy advanced algorithmic tools that underpin
-
to have a strong background in the foundations of machine learning. Special Instructions Required application documents include a cover letter, CV, a statement of research interests, and up to three
-
generative AI-based tools. Leverage recent breakthroughs in machine learning and natural language processing to build, test, and deploy advanced algorithmic tools that underpin rigorous empirical research in
-
modern spike sorting toolkits, machine learning or statistical modeling of neural data, and reproducible code practices (version control, documentation). · Background in neurodevelopmental