Postgraduate Scholarships
ESRC DTP Artificial Intelligence Studentship – Multi-view Representations for Pose Invariant Face Recognition in Man and Machine
- Reference
- SCI1848
- Closing Date
- Friday, 9th November 2018
- Department
- School of Psychology and School of Computer Science
School of Psychology and School of Computer Science, Nottingham University
This is a unique opportunity for a fully-funded ESRC Doctoral Studentship for applicants from the UK, EU or Overseas with a background in psychology, neuroscience, cognitive science, computer science or a related STEM discipline. The successful candidate will be located within the School of Psychology. The start date of this studentship may be 1st February 2019 or 1st October 2019 and will depend on the required award length (see ‘Award Lengths’ section below).
Pose-Invariant Face Recognition (PIFR) remains a significant stumbling block to realizing the full potential of face recognition as a passive biometric technology. This fundamental human ability poses a significant challenge for computer vision systems due to the immense within-class appearance variations caused by pose change, e.g., self-occlusion and coupled illumination or expression variations. Despite extensive efforts to solve the problem of pose-invariant face recognition it remains a significant barrier to developments in Artificial Intelligence. PIFR is achieved effortlessly by the human visual system but at present we do not understand the human system well enough to provide plausible solutions to the clear technological challenges. The aim of the studentship will be to enhance our understanding of how human observers achieve pose invariant recognition of faces in order to inform AI strategies. We will particularly focus on multi-view or pose-aware strategies and compare these against object-based models or pose-agnostic approaches. The work will involve both extensive psychophysical experimentation with human participants and computational experiments exploring computer models of pose-invariant dynamic face recognition. The project will be jointly supervised by Prof Alan Johnston (Psychology) and Dr Michel Valstar (Computer Science).
Award Lengths
The length of award offered will depend on the extent to which the candidate has met the ESRC’s core research methods training requirements. These are:
·Quantitative methods,
·Qualitative methods,
·Philosophy of Research and
·Research Design.
The extent to which you have met this criteria will be assessed during the application process. For those who have met all of the training, a +3 year award will be made, for those who have met some of the training, a 3.5 year award will be made, with a requirement that core training is completed within the first 12 months. If no core methods research has been undertaken by the candidate, then a +4 award will be made, which will include 180 credits research methods training before progressing to the PhD.
Owing to these requirements, +3 awards could start in February, but +4 awards would need to start at the beginning of the next academic year. +3.5 awards would depend on the type of training required and we will be able to advise candidates further prior to application if required.
You can read more about award lengths here .
Application Process
To be considered for this PhD, please complete the ESRC AI Studentship application form available online here with a covering letter and a CV as well as two references and then email this to [email protected] .
Deadline: Friday 9th November
Midlands Graduate School ESRC DTP
The Midlands Graduate School studentships cover fees and maintenance stipend and extensive support for research training, as well as research activity support grants. For this priority area candidates ordinarily resident in an EU member state will be eligible for a full award as will candidates from overseas.
Informal enquiries about the research can be directed to: [email protected] .
Postgraduate Scholarships
Classroom Assistant II (Part Time-4 Positions)
Position Details
Recruitment/Posting Title | Classroom Assistant II (Part Time-4 Positions) |
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Posting Number | 18TM0693 |
Department | Ctr-Strategic Urban Ldrshp-Cmd |
Overview | |
Posting Summary | The Classroom Assistant will support the classrooms serving children from ages 0-3 years and creating and maintaining a safe and stimulating environment for young children. This position is responsible for daily care of the children enrolled in his/her class. Responsibilities may include, but are not limited to, the following: physical caregiving, following an age appropriate daily plan, and facilitation of supportive relationships with co-workers, parents, and students. The Classroom Assistant II ensures, supports, and promotes each child’s safety, health, and development in cooperation with their families and other early childhood professionals in a manner consistent with NAEYC, NJDHS and child care licensing regulations |
Position Status | |
Hours Per Week | 19.5 |
Daily Work Shift | |
FLSA | Nonexempt |
Position Salary | $10-$12 per hour |
Payroll Designation | PeopleSoft |
Terms of Appointment | Temporary Staff Appointment – Hourly |
Minimum Education and Experience | AA degree, preferably in the field of Early Childhood Education of Child Development from an accredited public or private institution of higher education. Child Development Associate (CDA) credential for Preschool Caregivers required or an equivalent credential that addresses comparable competencies; or must obtain the credential within one year of employment as a Classroom Assistant II. |
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Preferred Qualifications | |
Required Knowledge, Skills, and Abilities | Must have (or be willing to obtain) training and experience necessary to develop consistent, stable, and supportive relationships with very young children. Ability to work as part of a multi-program/disciplinary team in providing a variety of services to children and families. Experience working with children from low income families. Valid First Aid/CPR card, food handler’s card, negative TB test, and clear criminal background check required. |
Equipment Utilized | |
Physical Demands and Work Environment | |
Special Conditions |
Posting Open Date | |
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Posting Close Date | |
Open Until Filled | No |
Special Instructions to Applicants | |
Regional Campus | Rutgers University-Camden |
Home Location Campus | Rutgers University-Camden |
Location Details |
Postgraduate Scholarships
Osteoporosis Prevention & Treatment Ctr Student Worker
Working Title | Osteoporosis Prevention & Treatment Ctr Student Worker |
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Anticipated Starting Academic Term | Fall |
Job Type | Student |
Job Category | Administrative/Office Support |
Federal Work Study Required? | No |
Job Summary | The student will be involved in patient relations, answer phones, scheduling patient appointments, study recruitment assistance, database entry, filing, copying, faxing |
Job Requirements | Prior customer service experience, familiarity or interest in medicine/medical terminology and Microsoft Office |
Child Protection Clearances | The following PA Act 153 clearances and background checks may be required prior to commencement of employment and as a condition of continued employment: PA State Police Criminal Record Check, FBI Criminal Record Check, PA Child Abuse History Clearance. |
Hourly Pay Rate | $7.65 |
Anticipated Number of Openings | 2 |
Anticipated Hours per Week | 10-20 |
Anticipated Weekly Schedule | flexible |
Campus | Pittsburgh |
Primary Work Location | Kaufmann Bldg, Suite 1110 |
Posting Number | S-07648-P |
The University of Pittsburgh is an Affirmative Action/Equal Opportunity Employer and values equality of opportunity, human dignity and diversity. EEO/AA/M/F/Vets/Disabled
Postgraduate Scholarships
Student Software Developer (FALL)
Student Software Developer (FALL) –
Job Number:
183298
Organization
: CIMMS
Job Location
: United States-Oklahoma-Norman
Schedule
: Part-time
Work Schedule: Flexible, 10-20 hours per week
Salary Range: $10.00
Benefits Provided: No
Required Attachments: Resume, Academic Transcripts, Class Schedule
Job Description
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The Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) seeks to fill a Student Assistant position to contribute to CIMMS Meteorological Phenomena Identification Near the Ground (mPING) project (http://mping.ou.edu/).
The principal duties of this position are:
Job Requirements
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Required Education: Must be currently enrolled in the current Fall 2018 Term as a student at the University of Oklahoma. Hiring contingent upon verification of current student status.
- Must attach Fall 2018 oZONE class schedule.
Skills:
- Strong computer programming skills with particular emphasis on Python and PostgreSQL
- Strong familiarity with the UNIX/Linux operating environment and web services such as Nginx, Django and RESTful web applications
Department Preferences:
- Optional experience with mobile app development on Android and/or iOS is a plus
- Experience debugging and/or trouble shooting software and hardware issues
- Experience working with complex software applications and web-based communications
- Excellent oral and written communication skills
- Ability to work both independently and cooperatively with others
Special Instructions: If you are selected as a final candidate for this position, you will be subject to The University of Oklahoma Norman Campus Tuberculosis Testing policy. To view the policy, visit https://hr.ou.edu/Policies-Handbooks/TB-Testing
Hiring contingent upon a Background Check?: Yes
Special Indications: None
Job Posting
: Oct 30, 2018
Unposting Date
: Ongoing