44 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" Postdoctoral positions at Nature Careers in United States
Sort by
Refine Your Search
-
machine learning techniques, will quantify groundwater recharge and groundwater resilience. Your responsibilities: Analyse the dynamics of hydrological connectivity of soil moisture using gridded soil
-
machine learning methods are a plus. Qualifications: PhD in neuroscience, or related fields DeepLabCut or similar methods Demonstrated hands-on experience with 2-photon imaging techniques Experience
-
, biochemical, cell, and tissue biology method skills. Experience in using computational analysis (biostatistics, machine learning, data science, physics, or a related field). We value diversity and strongly
-
of mitochondria in T cells and must have prior experience with mouse models and immunological techniques. They will have the opportunity to learn and perform LC-MS metabolomics using the Thermo Orbitrap Exploris
-
al., Nature Communications 2014; Martel et al., Journal of Neuroscience 2016). We also described epigenetic modifications and new gene targets of CREB-dependent transcription following learning
-
(e.g. Docker, Singularity) is desirable. Solid understanding of software development best practices (version control, testing, documentation). Mentoring Skills: Proven ability to mentor and teach others
-
, including CAR-T cell therapies. Qualifications: Applicants must hold an MD, PhD, or MD-PhD. A strong background in immunology, neuroscience, and/or cancer biology is essential. Prior experience with iPSCs
-
interested in implementation science, cancer prevention/control, and community-engaged research. To apply or learn more, please contact: Heather M. Brandt, PhD Director, HPV Cancer Prevention Program Member
-
. St. Jude trainees are able to learn from clinical and basic science investigators who work in close proximity and interact regularly to translate scientific discoveries into improved therapies
-
to independently design, execute, and troubleshoot experiments Strong computational skills for processing complex cryo-EM datasets Enthusiasm and demonstrated ability to rapidly learn new techniques Prior training