87 process-engineering "https:" "https:" "https:" "https:" "DESY" Postdoctoral positions at Rutgers University
Sort by
Refine Your Search
-
science and engineering. Eligible subject areas include computational biology and/or biomedicine, multi-modality fusion and inference (visual and NLP data), computationally efficient ML
-
engineering (i.e. CRISPR /Cas9), and broad use of molecular biology and biochemical tools to validate genomic alternations. The successful applicant is expected to independently conduct their own
-
Cancer Institute of New Jersey, Rutgers University, 164 Frelinghuysen Road, Piscataway, New Jersey 08854. Email: [email protected]. Lab website: https://sites.rutgers.edu/wei-xing-zong
-
Postdoctoral Associate to join the Addiction & Decision Neuroscience Lab ( https://www.konovalab.com/ ) led by Dr. Anna Konova and located at the Rutgers Center for Advanced Human Brain Imaging Research
-
required. Jain Lab website: https://thejainlab.org Position Status Full Time Posting Number 26FA0712 Posting Open Date 08/12/2026 Posting Close Date 08/12/2027 Qualifications Minimum Education and
-
be found at https://uhr.rutgers.edu/benefits/medical-plans ). Additional support is available for conference travel and professional development. The selected candidate will also be eligible for
-
be found at https://uhr.rutgers.edu/benefits/medical-plans ). Additional support is available for conference travel and professional development. The selected candidate will also be eligible for
-
innovative, multidisciplinary research at the intersection of neurophysiology, biomedical engineering, and rehabilitation within a stimulating, supportive, and mentored environment. Position Status
-
mathjobs.org https://www.mathjobs.org/jobs/Rutgers/PD27 and complete the application, with the requested supporting documents, for position PD27 under the Rutgers University-New Brunswick listing. All
-
publications can be found on his lab website: https://www.zhuhlab.com The candidates will focus on one or two of the following projects: Developing predictive toxicity models for assessing new