Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Nature Careers
- AIT Austrian Institute of Technology
- University of Vienna
- Universität Wien
- Academic Europe
- CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences
- Graz Medical University
- Johannes Kepler University
- Paracelsus Medical University
- University of Graz
- Universität Innsbruck
- 1 more »
- « less
-
Field
-
-haves: Completed Master's/Diploma degree in the field of biology First practice in scientific writing and with molecular-genetic research methods Didactic skills / experience in e-learning Strong IT user
-
awake behaving animals. Calcium imaging from ensembles of genetically-defined neuron populations and in vivo electrophysiology that allows for precise temporal resolution, are key techniques that provide
-
Offer Description Your Responsibilities Qualitative analysis of choice architectures and recommendation algorithms of social media platforms in the context of their communicative function within
-
for regenerative repair strategies. The successful candidate will work at the interface of tendon biology and tissue engineering, employing genetic mouse models and advanced experimental approaches. We are looking
-
to develop intelligent solutions in computer vision, robotics and control. We work closely with industrial and academic partners to bring cutting-edge algorithms onto real machines and into real environments
-
in Physics, Mathematics, Computer Science or a closely related field, ideally with a strong focus on quantum computing and numerical simulations. • Experience in data-reuploading quantum algorithms
-
quantum algorithms, optical quantum computing and quantum machine learning (highly desirable). • Experience in machine-learning schemes based on arrays of nonlinearly interacting mechanical oscillators
-
CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | 2 months ago
for biological discovery or graph-based methods for molecular and cellular networks. The technological foundation further consists of systems biology, virology, high-throughput genetics, genomics and proteomics
-
should focus on one or several of the following or related research areas: High-Throughput Sequencing Algorithms and Applications, Computational RNA Biology and Regulatory Genomics, Analysis and Modeling
-
intelligence, computer algebra, computational logic and automatic reasoning Experience with SAT, SMT, QBF, MaxSAT Experience with algorithmic methods for commutative and noncommutative polynomials Experience in