Postdoctoral Fellow (University of Texas Health San Antonio)
Are you excited about deep learning? Do you want to apply and develop deep learning methods to high dimensional neuroimaging data and make new discoveries which could advance our understanding of Alzheimer’s disease? We are looking for a postdoctoral fellow who is willing to research more deep and transfer learning methods in large cohort based studies.
Alzheimer’s disease and other dementias are heterogeneous conditions, which makes differentiating between them and their subtypes very challenging. Our goal is to use neuroimaging data and deep learning to help uncover and detect specific pathologies and patterns emerging in early Alzheimer’s disease. In this position your challenge will be to develop new deep learning architectures and algorithms that allow current pathology detection and prediction of possible future disease trajectories.
Your work environment will be the Neuroimage Analytics Laboratory (NAL, https://www.nallab.org) and the Biggs Institute Neuroimaging Core (BINC). We build advanced neuroimage analytical techniques to derive discovery. Data-driven approaches are of special interest in our lab, as machine learning and machine intelligence will guide the scientist towards the finding. On broader goal, our tools help delivering precise diagnostics on an individual’s level and ultimately could guide treatment progress.
We are part of the Biggs Institute (https://biggsinstitute.org), which is being established as a flagship, free-standing institute within University of Texas Health San Antonio (UTHSA), with the mission of establishing an interdisciplinary, integrated program to provide comprehensive clinical care and undertake innovative and important research into the prevention and treatment of Alzheimer’s Disease and other neurodegenerative conditions, including vascular contributions to dementia, Parkinson’s disease and frontotemporal dementia. It has strong institutional and community support and will benefit from existing resources within UTHSA such as the Barshop Institute for Longevity and Aging Studies, the Center for Biomedical Neuroscience, the School of Nursing, the Cancer Center, and the Research Imaging Institute along with the San Antonio campus of the UT Health Houston School of Public Health.
Responsibilities
• Develop, test and validate novel architectures and algorithms for deep learning with neuroimaging data
• Apply your validated methods to large scale research and real life everyday clinical routine neuroimaging data
• Willingness to work in teams, within NAL, BINC and Biggs and with national and international collaborators
• Communicate your research results to the larger communities through publications in international conferences and journals
• Work with great deal of independence in achieving research goals Requirements
• A PhD degree in Artificial Intelligence, Machine Learning, Computer Vision or Medical Image Analytics with solid experience in deep learning; Experience in Neuroimaging and Dementia Research is a plus.
• Great eagerness to solve scientific problems
• Strong programming skills, e.g. in Python, R, C++ and Java. Experience with
Python deep learning toolboxes and high-performance computational facilities
could be a plus;
• Excellent record of publishing in relevant high-quality journals in the above fields • Excellent communication abilities in English; spoken and written.
If interested, please send a copy of your CV to Dr. Habes (habes@uthscsa.edu)
Tenure Track Professors (W2) in computer science
November 24th, 2020 
Daniela Lopez de Luise We are looking for highly motivated young researchers in any modern area of Computer Science, especially in one or more of the following research areas:
* Artificial Intelligence, Machine Learning
* Natural Language Processing
* Data Science, Big Data
* Graphics, Visualization, Computer Vision
* Human-Computer Interaction
* Programming Languages and Software Engineering
* Computer Architecture and High-Performance Computing
* Networked, Distributed, Embedded, Real-Time Systems
* Bioinformatics
* Computational Logic and Verification
* Theory and Algorithms
* Societal Aspects of Computing
* Robotics
* Quantum Computing
The position will be established in the Department for Computer Science or in the Department for Language Science and Technology of Saarland University, which is part of the Saarland Informatics Campus (SIC), located in Saarbrücken. With its 800 researchers and more than 2.000 students from 81 countries, the SIC belongs to one of the leading locations for Computer Science in Germany and in Europe. All areas of computer science are covered at five globally renowned research institutes and three collaborating university departments, as well as in a total of 21 academic programs.
Our Offer:
Tenure track professors (W2) have faculty status at Saarland University, including the right to supervise bachelor’s, master’s and PhD students. They focus on world-class research, will lead their own research group and will have a significantly reduced teaching load. In case of outstanding performance, the position will be tenured as full professor (W3). The tenure decision is made after at most 6 years.
The position provides excellent working conditions in a lively scientific community, embedded in the vibrant research environment of the Saarland Informatics Campus. Saarland University has leading departments in Computer Science and Computational Linguistics, with more than 350 PhD students working on timely topics (see https://saarland-informatics-campus.de/ for additional information).
Qualifications:
Applicants must hold an outstanding PhD degree, typically have completed a postdoc stay and have teaching experience. They must have demonstrated outstanding research abilities and the potential to successfully lead their own research group. Active contribution to research and teaching, including basic lectures in computer science, is expected. Teaching languages are English or German (basic courses). We expect sufficient German language skills after an appropriate period.
Your Application:
Candidates should submit their application online at: https://applications.saarland-informatics-campus.de
No additional paper copy is required. The application must contain:
* a cover letter and curriculum vitae
* a full list of publications
* a short prospective research plan (2-5 pages)
* copies of degree certificates
* full text copies of the five most important publications
* a list of references: 3-5 (including email addresses), at least one of whom must be a person who is outside the group of your current or former supervisors or colleagues.
Applications will be accepted until December 11th, 2020. Application talks will take place between Feb. 01 and Feb. 26, 2021. Please refer to reference W1786 in your application. Please contact apply@saarland-informatics-campus.de if you have any questions.
Saarland University is an equal opportunity employer. In accordance with its policy of increasing the proportion of women in this type of employment, the University actively encourages applications from women. For candidates with equal qualifications, preference will be given to people with disabilities. In addition, Saarland University regards internationalization as a university-wide cross-sectional task and therefore encourages applications that align with activities to further internationalize the university.
When you submit a job application to Saarland University you will be transmitting personal data. Please refer to our privacy notice (https://www.uni-saarland.de/verwaltung/datenschutz/) for information on how we collect and process personal data in accordance with Art. 13 of the General Data Protection Regulation (GDPR). By submitting your application you confirm that you have taken note of the information in the Saarland University privacy notice.
Fwd: [CVML] [Conferences] Call for Participation—The 4th International Conference on Image and Graphics Processing (ICIGP 2021)
November 24th, 2020 Daniela Lopez de Luise Web: http://www.icigp.org
SPIE Conference—The 13th International Conference on Digital Image Processing (ICDIP 2021)
November 24th, 2020 Daniela Lopez de Luise IEEE CIS School ; Call for Book Chapters ;
November 21st, 2020 Daniela Lopez de Luise Dear Colleague,
We look forward to your participations in the following activities. You need to copy and paste the web addresses as hyperlinks have
been de-activated. Thank you.
1. IEEE CIS Summer School at IIT Indore: We’re delighted to inform that IIT Indore is organizing a 4 days IEEE Computational Intelligence Society (CIS) Summer School (online mode) on “Emerging Research Trends in Computational Intelligence – Theory and Applications” during November 26-29, 2020. Details of the summer school are available at http://events.iiti.ac.in/ieee-cis-summer-school/docs/CIS-Summer_School_Program_Schedule.pdf http://events.iiti.ac.in/ieee-cis-summer-school/registration
2. Call for Book Chapters (Springer Book): Handbook of Nature-Inspired Optimization Algorithms: The State of the Art Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems https://www3.ntu.edu.sg/home/epnsugan/index_files/HB-Vol-1.pdf
3. Call for Book Chapters (Springer Book): Handbook of Nature-Inspired Optimization Algorithms: The State of the Art Volume II: Solving Single Objective Constrained Real-Parameter Optimization Problems https://www3.ntu.edu.sg/home/epnsugan/index_files/HB-Vol-2.pdf
4. Three CEC 2021 Competitions with associated Special Sessions (SS-37 & SS-46) in Krakow, Poland in June-July 2021 ( https://cec2021.mini.pw.edu.pl/en ):
(a) Real-World Multiobjective Constrained Optimization: https://www3.ntu.edu.sg/home/epnsugan/index_files/CEC2021/CEC2021-1.htm
(b) Real Parameter Single Objective Bound Constrained Optimization: https://www3.ntu.edu.sg/home/epnsugan/index_files/CEC2021/CEC2021-2.htm
(c) Multimodal Multiobjective Path Planning Optimization: http://www5.zzu.edu.cn/ecilab/info/1036/1251.htm
5. Surveys & Benchmarks For Evolutionary & Swarm Algorithms:
https://www.ntu.edu.sg/home/epnsugan/index_files/surveys-tutorials.htm
https://www.ntu.edu.sg/home/epnsugan/index_files/cec-benchmarking.htm
6. Codes/software of our publications available for downloading:
https://www3.ntu.edu.sg/home/epnsugan/index_files/publications.htm
https://github.com/P-N-Suganthan
Thank you
Suganthan
https://www3.ntu.edu.sg/home/epnsugan/
https://github.com/P-N-Suganthan