COVID 19 contingencies for SOCS PGR students

Impact of Coronavirus- PGR Students

The rapidly developing situation will have implications for planned research activity and University of Lincoln are developing processes to minimise disruption to PGR student research work, progression and examination. For general impact on working or travel arrangements, please consult Foreign and Commonwealth Office and  websites, as these will provide regular updates. The following advice is specific the PGR study, and we shall provide further communications as situation develops.

If students are experiencing changes of circumstances, which may affect their research work, then first point of contact should be their supervisors and School PGR administrators.

Online communication such as email or tele/video-conferencing (e.g. skype) should be used in place of face-to-face meetings regarding progress in work. This can be reflected in monthly progress forms.

Where research work involves close contact with human participants, such as collection of samples or face to face interview, then these should be suspended. Alternative means of data collection, such as telephone, video conference or online questionnaire should be considered as replacements. For ethical approval, this will normally not require a re-submission of ethics forms, but students should inform their local ethics co-ordinators.

Changes to Planned Work

Where students are unable to continue with planned elements of work then the following principles should be considered:

  1. If disruption prevents planned element of project (such as data collection), but students can work on other areas of the project, such as analysis or writing up, then this can be reflected in a change to study plan and recorded in suitable PGR forms. For example, PGR Monthly Progress reports can capture short-term actions, whilst progression documents such as PGR Annual Report can capture significant changes to project aims and timelines.
  2. If students are unable to work on other areas of the project, then they can apply for interruption during a period of disruption. Normally students can only receive a total of 2 years interruption during a period of study, but we can consider extending this for those who have used up most of this allowance.
  3. If disruption risks student failing to submit a thesis within normal enrolment period (e.g. 4 years for full time PhD) then we can also consider no fee extensions to enrolment period.
  4. Where interruption has funding or visa implications, consult your supervisors and PGR administrators before applying.

 

With regards to PGR paperwork and assessment by School Progress Panels and CRDBs

Electronic submission of paperwork will be considered acceptable where submission of hard copies is not possible. This can be extended to electronic submission of the thesis so CRDBs can share with examiners during this period of disruption.

CRDBs can show discretion with regard to deadlines for key progression documents such as Confirmation of Studies, MPhil to PhD transfer and PGR Annual reports. Where disruption may cause delays in submission of these documents, then students should inform their local PGR Administrators, so that University can consider circumstances and advise on appropriate revised deadlines.

Examination of Masters by Research thesis for Computer Science Students

Masters by Research students can opt to be examined by viva/oral defence, with examiners providing written feedback on written work, and Masters by Research candidate addressing this feedback by correcting thesis as appropriate.   The School of Computer Science would still like to advise our students to have a viva where possible unless there is a strong reason for written feedback.  A viva will only be required where Masters by Research candidate or the examiners request this form of examination, in which case video or tele-conferencing should be used. An example of the process that is being trialled in College of Science is set out below.

Masters by Research Written Examination
The written component will take the form of a review, similar to those received when publishing a paper. Examiners (one internal and one external) will comment on the thesis independently in writing and suggest amendments. Once the internal has received amendments from the external, they will agree the outcome and this will be communicated to the student and supervisors by the internal. The communication will be in the form of a letter similar to that sent by journal editors.

Revisions will then be worked on within our standard timeframes. Students and examiners still have the option to request a viva should they want one. Should examiners not agree then the School PGR lead (or their deputy) will act as an intermediary.

Examination of PhD Thesis

PhD examinations should continue with oral defence, but using alternatives put in place of face-to-face meeting for viva such as video or tele conferencing (e.g. skype). Guidance on processes will be published next week.

Please also follow the guidance at https://doctoralschool.lincoln.ac.uk/coronavirus/ and talk to your supervisors.

Job Opportunity: Machine Vision Developer within B-hive Innovations

The Lincoln-based Agrifood-Tech company B-Hive is looking for a “Machine Vision Developer“:

logoA fantastic opportunity has arisen for the full-time permanent position of a Machine Vision Developer within B-hive Innovations.

This could be the perfect next step in your career and a chance to be at the forefront of developing the next generation of image-based solutions. You’ll be working on exciting and innovative projects to solve real day to day fresh produce and agricultural industry issues. Reporting to the Research and Development Project Manager and working closely with other B-hive team members, you will develop and support computer vision projects across the business.

Your responsibilities will include:

  • Researching and implementing machine vision techniques/methods for the fresh produce industry
  • Proposing and applying cutting–edge algorithms to add value to our projects and datasets
  • Converting research prototypes into production systems
  • Helping to deliver solutions to shape the future of technology in fresh produce
  • Transferring knowledge to other members of the team
  • Reading research papers

Required:

  • A PhD in computer vision and machine learning is preferred but master’s degree with relevant experience will also be considered
  • Strong coding skills C++, C#, and Python
  • Hands on experience with OpenCV
  • Experience with vision systems for object detection and image segmentation
  • Knowledge in structure motion, 3D reconstruction and machine learning
  • Ability to think outside the box and embrace new ideas
  • A willingness to pitch in with the team and get your hands dirty!

Some travel is involved, so you’ll need a full driving licence.

Hours: Monday to Friday 08:00 – 17:00. Weekend cover may also be required during the harvest season.

For further details or to apply please email info@b-hiveinnovations.co.uk

The Postgraduate Research Experience Survey for 2018 is now open!

The national Postgraduate Research Experience Survey (PRES) is run by the Higher Education Academy in conjunction with the university, and is the only UK higher education sector-wide survey to gain insight from postgraduate research students about their learning and supervision experience.

The survey is your opportunity to tell us of your experiences as a postgraduate researcher at the University of Lincoln, whether you are new or have nearly completed, are studying part- or full-time, for a Masters by Research, a PhD, or a professional doctorate. Your views matter to us and are crucial in ensuring that the University provides the experience postgraduate research students need, and to improve provision for current and future PGRs.

https://lincoln.onlinesurveys.ac.uk/pres2018

PGR meeting and Research Presentations – January 2017

Our monthly PGR meeting was held at Room MC3108 at 14:00 on Wednesday, 11th January.

We had have 1 speaker for this month seminar:

Speaker: Hussein Alahmer

Title: Computer-Aided Classification of Liver Lesions from CT Images Based on Multiple ROI

Abstract: This presentation introduces an automated Computer-Aided Classification (CAD) system to classify liver lesion into Benign or Malignant. The system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features from Multiple ROI, which is the novelty. Finally, classifying liver lesions into benign and malignant. The proposed system divides a segmented lesion into three areas, i.e. inside, outside and border areas. This is because the inside lesion, boundary, and surrounding lesion area contribute different information about the lesion. The features are extracted from the three areas and used to build a new feature vector to feed a classifier. The novelty lies in using the features from the multiple ROIs, and particularly surrounding area (outside), because the Malignant lesion affects the surrounding area differently compared to, the Benign lesion. Utilising the features from inside, border, and outside lesion area supports in better differentiation between benign and malignant lesion. The experimental results showed an enhancement in the classification accuracy (using multiple ROI technique) compared to the accuracy using a single ROI

The next seminar will be held in February. The date and venue for the next meeting will be announced.