Joint post-doc call of the projects FWF SFB 65 "Taming Complexity in Partial Differential Systems" and ERC Advanced Grant "Emerging Network Structures and Neuromorphic Applications"
We are currently advertising
2 post-doc positions
in the framework of the following projects:
- Project Part 14 (Sara Merino Aceituno & Christian Schmeiser) in the FWF SFB 65 "Taming Complexity in Partial Differential Systems" (a large-scale project focusing on the solution of PDEs describing the behavior of complex systems from Physics, Biology, and Technologies);
- ERC Advanced Grant "Emerging Network Structures and Neuromorphic Applications" of Prof. Ansgar Jüngel.
The deadline for both applications is on
23.04.2023 (23:59 Europe/Vienna time)
.
Type of employment
Both positions are post-doc positions with an annual salary of approximately 60k € gross
(corresponding to approx. 40k € net salary / year).
Positions
POSITION 1
Theme:
Emergent properties in models for collective dynamics
Scientific context:
Collective dynamics is ubiquitous in nature. We are interesting in understanding the emergence
of large patterns from individual particle systems. The project can involve numerical simulations
and analysis of partial-differential equations for collective dynamics, like investigating
existence of solutions, qualitative properties of these solutions, derivation of the equations, and long-time behavior.
This project (Project Part 14) is part of the Project SFB 65 "Taming Complexity in Partial Differential Systems" financed by the Austrian Science Fund (FWF).
Duration of employment:
This position is financed until the end of the current SFB financing period (28.02.2025)
and it could be extended for one more year.
Affiliation:
the successful applicant will be employed at the
Faculty of Mathematics
of the
University of Vienna (Austria)
and will be associated to the
workgroup of Sara Merino Aceituno.
Contact:
for queries on this position, please contact
Assoc.-Prof. Sara Merino Aceituno at sara.merino@univie.ac.at.
POSITION 2
Theme:
Numerical approximation of drift-diffusion equations for memristor devices
Scientific context:
Memristors are emerging neuromorphic devices that simulate synapses of the brain.
The project goal is the design of efficient numerical approximations of drift-diffusion equations
for the charge transport in memristors, using for instance finite-volume,
mixed finite-element or mixed discontinuous Galerkin methods.
The tasks are the existence of discrete solutions, proof of their qualitative properties,
convergence of the scheme, and numerical implementation of the scheme in two space dimensions.
This project is financed by the ERC Advanced Grant "Emerging Network Structures and Neuromorphic Applications".
Duration of employment:
1 year (extension to 2 years is possible).
Affiliation:
the successful applicant will be employed at the
Institute of Analysis and Scientific Computing
of
TU Wien (Vienna, Austria)
and will be associated to the
workgroup of Ansgar Jüngel.
Contact:
for queries on this position, please contact
Prof. Ansgar Jüngel at juengel@tuwien.ac.at.
Skills required:
Applicants must have or be close to obtain a PhD in Mathematics.
An excellent track record and a strong background in nonlinear partial differential equations
and numerical analysis are required.
Preferred start date
As soon as possible.
Requested documents
- A motivation letter.
- A single pdf with the CV and list of publications.
- A pdf or a link to the PhD thesis. Only in case you have not a finished thesis yet, please upload either a draft (specifying in the first page that this is a draft) or an abstract of the planned content that will be part of your thesis.
Additional requested information
Contact details of 2 possible references (recommendation letters do not need to be submitted during the online application).
Candidates for this position are requested
to fill the application form at
this link.
You can choose to candidate for both advertised positions, or just to one of them.
We are committed to diversity and inclusion; all qualified applicants will receive consideration for employment without regard to gender, gender identity or expression, sexual orientation, religion, national origin, disability, or age.
The personal data submitted for this application will be treated according to the European General Data Protection Regulation (GDPR). A
Privacy and Data Protection Policy
for this call is available
at this link.
General inquiries for this call (in particular: questions related to the online application) can be directed to the Scientific Manager of the SFB 65 (Matteo Tommasini, at matteo.tommasini@univie.ac.at).