May 2018 - Comp-neuro - lists.cnsorg.org

Postdoc position in neuronal mechanism of episodic memory at Max Planck Florida Institute for Neuroscience
by Yingxue.Wang＠mpfi.org 23 May '18

23 May '18

*** Apologies for cross posting*** Postdoctoral Fellow Summary The Wang Lab at the Max Planck Florida Institute for Neuroscience (links to website<https://yingxuewang.org/>) is inviting applications for postdoctoral positions. Our group seeks highly motivated and independent individuals to join our effort focused on the neuronal mechanisms of learning and episodic memory. Essential Duties & Responsibilities The Wang Lab investigates the circuit underpinnings of episodic memory. In particular, we intend to isolate the hippocampal neuronal activities that are independent of sensory inputs and potentially represent memory traces. We seek to understand how elements of the hippocampal circuit cooperate to generate the internally generated neuronal activities and support the formation and retrieval of memory. Our investigation employs a combination of in vivo electrophysiological, advanced two-photon imaging, optogenetic, and pharmacological approaches, and couples experiments with computational modeling. We encourage applications from candidates who are interested in applying multidisciplinary approaches to examine circuit mechanisms of memory. Education and/or Experience The ideal candidates should have an upcoming or recent Ph.D. or MD/Ph.D. in neuroscience or related fields. Candidates holding a Ph.D. in electrical engineering, biomedical engineering, computer science, or physics and interested in understanding the neuronal mechanisms of learning and memory are also welcome to apply. Previous experience with in vivo electrophysiology and/or two-photon imaging, quantitative data analysis and computer programming is highly preferred. Excellent communication skills and an ability to work well in a team are required. Additional Information Max Planck Florida Institute for Neuroscience is part of the Jupiter Neuroscience Research Campus that also includes the Scripps Research Institute Florida and Florida Atlantic University. It provides a flourishing interdisciplinary research environment for neuroscience. We offer outstanding benefits and salary compensation above the NIH scales. Interested candidates are encouraged to send the following documents to Dr. Yingxue Wang (email address: Yingxue.Wang(a)mpfi.org<mailto:Yingxue.Wang@mpfi.org>): - Curriculum vitae with a list of publications - A statement of research experiences and interests (1-2 pages) - The names and contact information of three references Personal contact can be addressed to the above email address prior to the application.

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PhD studentships in Neuromorphic computing and Data Science
by Schmuker, Michael 23 May '18

23 May '18

We are offering a several PhD studentships in the Biocomputation group at the University of Hertfordshire. Details here: https://www.herts.ac.uk/__data/assets/pdf_file/0007/209365/Data-Science-and… Our group translates processes from the brain into algorithms for efficient computing. A particular area of interest is Neural Data Science, where we extract information from complex data sets obtained in neuroscience. Our goal is to shed light on how the brain is processing information and to cast this knowledge into efficient algorithms for pattern recognition and signal processing. We implement such algorithms by leveraging so-called neuromorphic hardware, i.e., specialised computer chips that mimic the massively parallel architecture of the brain, which greatly accelerate brain-inspired neural computing. We are looking for highly motivated candidates with a keen interest in squeezing every bit of information out of complex data sets, to understand how the brain copes with the relentless onslaught of sensory information, and to implement those aspects on a new computer architecture. A diverse choice of topics is available, including but not limited to: • Data mining in neuronal imaging using matrix factorisation and machine learning • Brain-inspired pattern recognition using supervised and unsupervised learning • Olfaction-inspired signal processing and odor recognition for electronic gas sensors It is also possible to suggest topics. Candidates should have excellent programming skills and also some experience in data mining. Previous exposure to low-level hardware programming (e.g. microcontrollers, GPUs) and/or computer engineering is a plus. We collaborate with world-leading neuroscience labs in the UK and abroad to investigate how the brain is processing dynamic sensory information. As a member of the Human Brain Project we pioneer the use of neuromorphic hardware for Data Science. This guarantees a stimulating research environment for a project that aims not only at generating theoretical insight but also validating the findings with experimental scientists and pursuing applications in the real world. Successful candidates are eligible for a research studentship award from the University (approximately GBP 14,777 per annum bursary plus the payment of the standard UK student fees). Applicants from outside the UK or EU are eligible, but will have to pay half of the overseas fees out of their bursary. Please contact Principal Investigator Dr. Michael Schmuker prior to application to scope out a project proposal that is tailored to your background, via email: m.schmuker(a)herts.ac.uk. More info and instructions how to apply are available at https://www.herts.ac.uk/study/schools-of- study/computer-science/our-research/the-phd-programme-in-computer-science . The next short-listing process for studentship applications will begin on 25 June 2018. — Dr Michael Schmuker AFHEA Reader in Data Science Biocomputation Group University of Hertfordshire http://biomachinelearning.net

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PhD position in systems/computational neuroscience, Leicester, UK
by Okun, Michael (Dr.) 22 May '18

22 May '18

A PhD position is available at Centre for Systems Neuroscience, Leicester, UK. The project will focus on organisation and mechanisms of resting state cortical dynamics, particularly in the infraslow (0.01 - 1 Hz) timescales. Additional details are available at https://www.findaphd.com/search/ProjectDetails.aspx?PJID=97389 or by contacting Michael Okun (m.okun(a)le.ac.uk). The deadline for applications is 7th of June.

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OMG- Emotion Recognition Challenge - Final Results
by Pablo Barros 22 May '18

22 May '18

Dear all, I would like to share with you all the results of our first OMG- Emotion Recognition Challenge. Our challenge is based on the One-Minute-Gradual Emotion Dataset (OMG-Emotion Dataset), which is composed of 567 emotion videos with an average length of 1 minute, collected from a variety of Youtube channels. Each team had a task to describe each video with a continuous space of arousal/valence domain. The challenge had a total of 34 teams registered, from which we got 11 final submissions. Each final submission was composed of a short paper describing the solution and the link to the code repository. The solutions used different modalities (ranging from unimodal audio and vision to multimodal audio, vision, and text), and thus provide us with a very complex evaluation scenario. All the submissions were based on neural network models. We split results into arousal and valence. For arousal, the best results came from the GammaLab team. Their three submissions are our top 3 CCC arousal, followed by the three submissions from the audEERING team, and the two submissions from the HKUST-NISL2018 team. For valence, the GammaLab team stays still in first (with their three submissions), followed by the two submissions of ADSC team and the three submissions from the iBug team. Congratulations to you all! We provide a leaderboard on our website ( https://www2.informatik.uni-hamburg.de/wtm/OMG-EmotionChallenge/ ), which will be permanently stored. This way, everyone can see the final results of the challenge, have a quick access to a formal description of the solutions and to the codes. This will help to disseminate knowledge even further and will improve the reproducibility of your solutions. We also provide a general leaderboard which will be updated constantly with new submissions. If you are interested in having your score in our general leaderboard, just send us an e-mail following the instructions on our website. I would also to invite you all to the presentation of the challenge summary during the WCCI/IJCNN 2018 in Rio de Janeiro, Brasil. Best Regards, Pablo -- Dr. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.de https://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.html https://www.inf.uni-hamburg.de/en/inst/ab/wtm/

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Call for Papers: Special Session on Computational Methods for Neuroimaging Analysis, 6-8 September, Portugal
by Tiago Azevedo 22 May '18

22 May '18

Dear all, Below find the call for papers for the special session "Computational Methods for Neuroimaging Analysis". It will be be held during the 15th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics, at Caparica, Portugal, from 6 to 8 September. **Important Dates** Paper submission deadline: 10 June 2018 Acceptance notification: 9 July 2018 Author registration due: 20 July 2018 Camera ready due: 29 July 2018 Conference: 6-8 September 2018 **Link** https://eventos.fct.unl.pt/cibb2018/pages/special-sessions **Aim and scope** There is an increasing need for the application of machine learning (ML) techniques which can perform image processing operations such as segmentation, coregistration, classification and dimensionality reduction in the field of neuroimaging. Although the manual approach often remains the golden standard in some tasks (like segmentation), ML can be utilised to automate and facilitate the work of researchers and clinicians. Frequently used techniques include support vector machines (SVMs) for classification problems, graph-based methods for brain network analysis and recently artificial neural networks (ANNs). Deep ANNs, i.e. deep learning, have proved to be very successful in computer vision tasks owing to the ability to automatically extract hierarchical descriptive features from input images. It has also been used in the medical and neuroimaging domains for automatic disease diagnosis, tissue segmentation and even synthetic image generation. The issue, however, is the relative sample paucity in typical neuroimaging datasets which leads to poor generalisation considering the high number of parameters employed in typical deep neural networks. Consequently, parameter- efficient design paradigms ought to be created. Another approach to investigate degeneration is the study and mapping of the neural connections in the brain known as the connectome. The connectome can be seen as a matrix representing all possible pairwise connections between different neural areas. Researchers study both the structural and functional connectivity in order to understand important brain patterns, such as how the connectome impacts the dynamics of disease spreading, ageing and learning. Topics of interest includes but are not limited to: • Machine learning techniques for segmentation, coregistration, classification or dimensionality reduction of neuroimages   • Deep learning for neuroimaging analysis   • Brain network analysis   • Applications of graph theory to MRI and fMRI data   • Applications of machine learning methodologies for neurodegenerative disease studies   • Computational modelling and analysis of neuroimaging   • Methods of analysis for structural or functional connectivity   • Development of new neuroimaging tools **Session chairs** Tiago Azevedo, University of Cambridge, UK Giovanna Maria Dimitri, University of Cambridge, UK Pietro Liò, University of Cambridge, UK Angela Serra, University of Salerno, Italy Simeon Spasov, University of Cambridge, UK

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Two postdoc positions at Champalimaud Centre for the Unknown, Lisbon
by Christian Machens 21 May '18

21 May '18

POSTDOC POSITIONS IN COMPUTATIONAL / SYSTEMS NEUROSCIENCE Two postdoctoral positions - one in theory and one in experiment - are available in a joint project between the labs of Alfonso Renart and Christian Machens at the Champalimaud Centre for the Unknown in Lisbon, Portugal. Location: The Champalimaud Centre for the Unknown is situated on the waterfront in central Lisbon. English is the official language of the Centre. The center is composed of about 20 main research groups who study diverse topics in neuroscience using advanced, cutting edge techniques. Project: The proposed project will investigate to what extent neural circuits actively compensate random perturbations. The project involves the recordings and partial silencing of neural populations, population-level analysis using dimensionality reduction and other techniques, and the modeling of the results with spiking networks. Relevant background literature: Renart, de la Rocha, et al (2010), Science 327:587-90; Barrett et al (2016), eLife 5:12454; Deneve and Machens (2016), Nat Neurosci 19:375-82. Profile (theory): The ideal candidate should have a PhD with a strong, quantitative background (ideally in fields such as machine learning and/or computational neuroscience). The position is funded for two years with possibility of extension. Profile (experiment): The ideal candidate should have experience in electrophysiology (e.g. recordings from behaving head-fixed mice) and data analysis (e.g. dimensionality reduction methods etc). Applications should include a CV, a statement of research interests (max 1 page), and two letters of recommendation. Feel free to ask any informal questions about the positions if you are interested. Electronic submissions in pdf-format are preferred and should be send to both of the following email addresses: christian.machens(a)neuro.fchampalimaud.org alfonso.renart(a)neuro.fchampalimaud.org

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project in neuromath & circuit-based neuron classification
by NeuroMorpho Administrator 21 May '18

21 May '18

Dear colleagues, Please find below an advertisement for a postdoc position in my lab. Thanks in advance for spreading the opportunity! Giorgio Ascoli Postdoctoral Research Fellow - Department of Bioengineering The George Mason University Department of Bioengineering, within the Volgenau School of Engineering, is seeking a postdoctoral research fellow to contribute to ongoing cutting-edge neuroinformatics research funded by the National Institutes of Health (NIH) under the BRAIN initiative. George Mason University has a strong institutional commitment to the achievement of excellence and diversity among its faculty and staff, and strongly encourages candidates to apply who will enrich Mason’s academic and culturally inclusive environment. Responsibilities: The initial focus is on quantitative analysis, modeling, and simulations of neuronal classification, network connectivity, and circuit dynamics. Post-doc will join the Center for Neural Informatics, Structures, and Plasticity (CN3) in George Mason University’s Volgenau School of Engineering in northern Virginia (20 miles west of Washington DC). CN3 is an interdisciplinary, energetic, and creative research group in the Krasnow Institute for Advanced Study of the main Fairfax campus. The position entails tight collaborations with faculty and trainees in the Bioengineering, Neuroscience, and Mathematics programs. The successful applicant will work directly with the CN3 director and will have unlimited access to dedicated supercomputer and server facilities, flexible working schedule, salary based on the NIH postdoctoral scale, and state employee benefits. Required Qualifications: The successful candidate is expected to have a Ph.D. in a discipline related to biomedical engineering, applied mathematics, computer science, neuroscience, physics, data science, or related fields. Preferred Qualifications: The incumbent should have research experience with programming and scripting languages (C++, Java, R, MatLab). Working knowledge of network neuroscience, clustering techniques, statistics, graph theory, and/or machine learning are desirable. About Mason: George Mason University, a tier-1 research institution, is considered one of the top “Up and Coming” educational institutions in America by the U.S. News and World Report. It is conveniently located in the Washington D.C., metropolitan area within easy access to several national laboratories and research centers (including the National Institutes of Health and the Janelia Research Campus of the Howard Hughes Medical Institute), and provides a highly stimulating environment for interdisciplinary science. Biomedical research is a major area of strategic focus for Mason, and the Center for Neural Informatics has been at the forefront of computational neuroscience research since its establishment in 2006. For full consideration, applicants must complete and submit the online application at https://jobs.gmu.edu/postings/42954 [http://jobs.gmu.edu/hr/assets/social_share.jpg]<https://jobs.gmu.edu/postings/42954> Postdoctoral Research Fellow<https://jobs.gmu.edu/postings/42954> jobs.gmu.edu Postdoctoral Research Fellow, Department of Bioengineering The George Mason University Department of Bioengineering, within the Volgenau School of Engineering, is seeking a postdoctoral research fellow to contribute to ongoing cutting-edge neuroinformatics research funded by the National Institutes of Health (NIH) under the BRAIN initiative. George Mason University has a strong institutional commitment to the achievement of excellence and diversity among its faculty and staff, and strongly encourages candidates to apply who will enrich Mason’s academic and culturally inclusive environment. Responsibilities: The initial focus is on quantitative analysis, modeling, and simulations of neuronal classification, network connectivity, and circuit dynamics. Post-doc will join the Center for Neural Informatics, Structures, and Plasticity (CN3) in George Mason University’s Volgenau School of Engineering in northern Virginia (20 miles west of Washington DC). CN3 is an interdisciplinary, energetic, and creative resea Finalist will be required to submit three letters of recommendation upon request. Review of applications will begin on June 1, 2018, and continue until the position is filled. This position will be renewed annually subject to satisfactory performance and availability of funds. Non-resident aliens are welcome to apply. Questions regarding the position should be directed to ascoli(a)gmu.edu<mailto:ascoli@gmu.edu> George Mason University is an equal opportunity/affirmative action employer, committed to promoting inclusion and equity in its community. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, disability, or protected veteran status. ---------------- Giorgio Ascoli, PhD University Professor Bioengineering Department, Volgenau School of Engineering Neuroscience Program, Krasnow Institute for Advanced Study Director, Center for Neural Informatics, Structures, & Plasticity MS2A1 - George Mason University, Fairfax, VA 22030-4444 Ph. +1(703)993-4383/+1(703)673-8894 Author of “Trees of the Brain, Roots of the Mind” (MIT Press, 2015) Founding Editor-in-Chief, Neuroinformatics

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Project in neurotechnology/vision in mice in the Roelfsema lab - Amsterdam
by Pieter Roelfsema 21 May '18

21 May '18

Dear colleagues, Please find below an advertisement for a PhD or postdoc position in my lab. Thanks for spreading the advertisement! Pieter Roelfsema A postdoc or PhD-student position is available in the Vision & Cognition group at the Netherlands Institute for Neuroscience in Amsterdam. The aim is to understand visual perception and plasticity elicited by electrical stimulation of the visual cortex in mice, with the ultimate aim to create a visual cortical prosthesis to restore a rudimentary form of vision for the blind. Project description: Visual perception elicited by electrical stimulation of mouse visual cortex Electrical stimulation of the visual cortex elicits a “phosphene”, an artificial percept of light. By stimulating multiple electrodes at the same time, it might prove possible evoke pattern vision. The aims of this project are to (1) develop new methods for electrical stimulation in mice; (2) to study the patterns of activated neurons using two-photon imaging and (3) to test visual perception of electrical percepts and its plasticity in mice. Qualifications We will consider highly motivated, self-driven candidates with a degree in neuroscience, (neuro)psychology, biomedical sciences, natural sciences, material science, mathematics, physics, etc. A high level of written and spoken English and good programming skills are required. The ideal candidate will have experience with neurophysiological techniques, the analysis of neuronal activity in alert animals, and a background in neuroscience. Interest in the translation of fundamental research into clinical applications and collaboration with high-tech companies is a plus. All qualified applicants will receive consideration for employment without regard to race, religion, sexual orientation, nationality, disability, etc. Appointment The position involves a fulltime temporary appointment for 3 years (postdoc) or 4 years (PhD student). Starting date: Mid-2018. Salary PhD position: The gross monthly salary coming with a full-time appointment will amount to a minimum of € 2.191 in the first year to € 2.801 in the fourth year (P scale of the Collective Labour Agreement for Dutch Universities). Postdoctoral position: This will be commensurate with experience and institutional guidelines based on the Collective Labour Agreement for Dutch Universities; CAO NU). In addition, an 8% holiday allowance and 8.3% year-end bonus will be provided. We offer an extensive package of fringe benefits. To apply, please send an application letter, CV, and two letters of recommendation to: Tini Eikelboom The Netherlands Institute for Neuroscience Meibergdreef 47, 1105 BA Amsterdam, The Netherlands Telephone: +31-20-5664587 E-mail: t.eikelboom(a)nin.knaw.nl<mailto:t.eikelboom@nin.knaw.nl> Evaluation of candidates will begin immediately, and continue until the position is filled. We aim to fill the position mid-July 2018.

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[job] PhD position opening in Machine Learning for Adaptive Language interaction with an intelligent dialog companion.
by Pierre-Yves Oudeyer 18 May '18

18 May '18

*Title: Machine Learning for Adaptive Language interaction with an intelligent dialog companion *Keywords: Deep reinforcement learning, interactive machine learning, natural language processing, neural networks, intelligent dialog companion *Context: The thesis takes place in the context of a collaboration between the Robot Cognition Laboratory (INSERM/CNRS), the innovation services department of Intrinsic Cloud Temple, and the Flowers laboratory (Inria). *Background: Based on RCL experience in human-robot cooperation and learning, we have developed an intelligent agent that accompanies humans in their experience using web-based tools, learns from explicit demonstration, and allows the user to re-use and recompose learned plans to form more complex structured plans. *Project: For the moment, the system learns from demonstration. The project will extend and study algorithms for interactive machine learning (using Deep RL) to include language instructions as one of the ways that the system can learn, that is, by using the invariant structure of the human verbal description to organize procedural representations. This will advance the state of the art in the integration of language into reinforcement learning systems. * Location: Lyon and Nanterre, France (Inserm and Cloud Temple) * Response modalities: Send (1) a letter of motivation stating your interest in the project, (2) a CV, and (3) two letters of recommendation to the three addresses for Jean-Michel Dussoux, Peter Ford Dominey, and Pierre-Yves Oudeyer listed in the call, with the subject [Intelligent Assistant PhD]. jmd(a)intrinsec.com; pierre-yves.oudeyer(a)inria.fr; peter.dominey(a)inserm.fr More details: https://www.dropbox.com/s/g5ksylrrlgatkf2/RCL-CT-THESE-interaction-manager-…

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POSITIONS: Lecturer/Associate Professor in Robotics, School of Computing, Electronics and Mathematics, University of Plymouth, UK
by Roman Borisyuk 18 May '18

18 May '18

Dear colleagues, The University of Plymouth is seeking to fill two positions as Lecturer/Associate Professor in Robotics. General Description The School offers a wide range of degree programmes related to Technology in the areas of Robotics, Electrical & Electronic Engineering, Computer Science and Mathematics. We provide a stimulating teaching and research environment with strong connections to business and industry and offer excellent employment prospects for our graduates. We have a well-established interdisciplinary research base which covers: Centre for Robotics and Neural Systems (CRNS); Security, Communications & Networks; Nanotechnology & Electronics Research and Development. Four current active areas of research in Plymouth are the design and construction of agricultural robots for fruit and vegetable harvesting; the study of human-robot interaction and collaboration; the computational modelling and development of manipulation systems based on experimental investigations of human motor control and the design and development of robotic applications for Urban Search & Rescue and Nuclear Decommissioning. We have vacancies for enthusiastic, innovative and dynamic individuals to join our vibrant School to support Robotics and Machine Learning, especially as applied to solving real-world problems by building systems that can operate near people. Areas of interest include (but are not limited to) aspects of robotics systems such as sensors and actuators, kinematics and dynamics, autonomous mobile platforms and deep learning for control and recognition. Required qualifications Applications are invited from academics and/or professional engineers, who can demonstrate a commitment and enthusiasm for innovation in higher education and to the development of the next generation of Robotic Engineers. You must have undergraduate and postgraduate degrees in relevant disciplines (such as Engineering/Maths/Physics/Computer Science) together with an international profile and reputation for research excellence. We offer * Salary: from £33,518 to £56,950 (Grade 7/8/9) depending on the candidate's qualification and the level of experience * Contract Type: full-time, working 37 hours per week on a permanent basis Duties and responsibilities As well as carrying out cutting edge research, you will supervise and contribute to training of Research Assistants (RAs) and PhD students, as well as contributing to teaching on the undergraduate and postgraduate Robotics programmes, as well as other courses within the School. The Electronics and Robotics subject groups are renowned for excellence in producing high quality hands-on engineers and you should be able to support practical hardware and software projects. How to apply Candidates can apply online by visiting the application link below: http://www.jobs.ac.uk/job/BJS594/lecturer-associate-professor-in-robotics/ Contact for informal discussion: For informal queries, do not hesitate to contact Dr Ian Howard (ian.howard(a)plymouth.ac.uk<mailto:ian.howard@plymouth.ac.uk>). Further information about the school and its courses is available at: www.plymouth.ac.uk/compmath<http://www.plymouth.ac.uk/compmath>, with details of our research centre available at: www.plymouth.ac.uk/research/crns<http://www.plymouth.ac.uk/research/crns> Closing date: 12 midnight, Thursday 31 May 2018. University of Plymouth is committed to an inclusive culture and respecting diversity and welcomes applications from all sections of the community and is a Stonewall diversity champion. The University holds a Bronze Athena SWAN Award which recognises commitment to advancing women’s careers in STEMM academia. University of Plymouth has been recognised by Bloomberg as one of the 50 best UK employers for 2016. Dr Mario Gianni Lecturer in Computer Science School of Computing, Electronics and Mathematics Faculty of Science and Engineering Plymouth University A221 Portland Square Drake Circus, Devon PL48AA, UK +44(0)1752 586318<tel:+44%201752%20586318> ________________________________ [http://www.plymouth.ac.uk/images/email_footer.gif]<http://www.plymouth.ac.uk/worldclass> This email and any files with it are confidential and intended solely for the use of the recipient to whom it is addressed. If you are not the intended recipient then copying, distribution or other use of the information contained is strictly prohibited and you should not rely on it. If you have received this email in error please let the sender know immediately and delete it from your system(s). Internet emails are not necessarily secure. While we take every care, Plymouth University accepts no responsibility for viruses and it is your responsibility to scan emails and their attachments. Plymouth University does not accept responsibility for any changes made after it was sent. Nothing in this email or its attachments constitutes an order for goods or services unless accompanied by an official order form. ========================================================== This email comes from the euRobotics mailinglist. You can edit your personal mailinglist profile (including unsubscription) via https://lists.iais.fraunhofer.de/sympa/info/euron-dist ________________________________ [http://www.plymouth.ac.uk/images/email_footer.gif]<http://www.plymouth.ac.uk/worldclass> This email and any files with it are confidential and intended solely for the use of the recipient to whom it is addressed. If you are not the intended recipient then copying, distribution or other use of the information contained is strictly prohibited and you should not rely on it. If you have received this email in error please let the sender know immediately and delete it from your system(s). Internet emails are not necessarily secure. While we take every care, Plymouth University accepts no responsibility for viruses and it is your responsibility to scan emails and their attachments. Plymouth University does not accept responsibility for any changes made after it was sent. Nothing in this email or its attachments constitutes an order for goods or services unless accompanied by an official order form.

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