Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Germany
- France
- United Kingdom
- Sweden
- Spain
- Netherlands
- Portugal
- Singapore
- Belgium
- Norway
- Denmark
- Poland
- Austria
- Australia
- United Arab Emirates
- Switzerland
- Canada
- Czech
- Finland
- Italy
- Luxembourg
- Ireland
- Hong Kong
- China
- Romania
- Estonia
- Morocco
- Brazil
- Cyprus
- Latvia
- Japan
- Croatia
- Lithuania
- New Zealand
- Bulgaria
- Greece
- Kuwait
- Slovakia
- Andorra
- Europe
- Iceland
- India
- Malta
- Slovenia
- Worldwide
- 36 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Biology
- Economics
- Science
- Mathematics
- Materials Science
- Business
- Chemistry
- Environment
- Earth Sciences
- Psychology
- Linguistics
- Electrical Engineering
- Arts and Literature
- Humanities
- Education
- Physics
- Social Sciences
- Law
- Sports and Recreation
- Design
- Philosophy
- Statistics
- 15 more »
- « less
-
development, optimization, and continuous learning in a rapidly evolving field. Desirable: experience with multi‑omics datasets, single‑cell or spatial technologies, or basic scripting skills (R/Python). Our
-
analysis or modelling tools—such as Aspen Plus, Matlab/Python, or similar—to help link experimental findings to process or techno‑economic evaluations. What you will do Take courses at an advanced level
-
skills. Is confident using digital learning tools such as Python, SAS, Stata or similar. Holds (or will soon complete) a doctorate in Finance or a closely related field. Enjoys contributing to the wider
-
of the most recent econometric methods to study the evolution of wealth accumulation from incomplete tax data. The applicant needs to have advanced programming skills in Stata, R and Python
-
Python and PyTorch Assist in dataset preparation, preprocessing, and augmentation Run training and evaluation pipelines Analyze experimental results and document findings Collaborate closely with graduate
-
metabolite analysis You have good skills in the use of R for statistical data analysis and Python programming Any teaching experience or participation in extra training, conferences, etc. is recommended You
-
. Practical experience applying machine learning or deep learning methods to biological data. Proficient in Python, with working knowledge of bash and experience using HPC or cluster environments (e.g. SLURM
-
of machine learning or quantum computing Programming skills in Python and/or C/C++ Experience with scientific software tools and numerical libraries Familiarity with Linux-based computing environments Ability
-
for our multidisciplinary research focusing on transportation safety and mobility (http://umtri.umich.edu ). Established in 1965, we maintain the highest standards of excellence as we conduct research
-
methodological training in (bio)statistics and/or machine learning Interest in developing rigorous methods for biomedical, clinical, or public health data Experience with statistical computing (R and/or Python