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Postdoctoral positions in the Geffen lab at the University of Pennsylvania
by Maria Geffen June 22, 2021

June 22, 2021

The Geffen laboratory <http://hosting.med.upenn.edu/hearing> at the University of Pennsylvania <http://www.upenn.edu/> has multiple postdoctoral positions open in systems neuroscience with the broad goal of understanding the neuronal circuits for auditory perception and learning. We are looking for energetic and talented scientists interested in studying the function of the brain. The postdoctoral fellow will have the opportunity to learn and apply a host of systems neuroscience techniques, including two-photon imaging of population activity, optogenetic manipulations, large-scale electrophysiology and behavior in mice. Prior experience with some of these methods is preferred, but not required. Depending on the candidate’s interests, all projects provide an opportunity to learn and apply advanced computational methods, including dynamic systems analysis of neuronal population activity; Bayesian approaches for understanding the relation between neuronal activity and behavior; machine learning methods to understand large-scale neuronal activity. We currently have openings for postdoctoral fellows for three projects: (1) Neuronal mechanisms for predictive coding: Auditory perception relies on predicting statistics of incoming signals, be it identifying the speech of a conversation partner in a crowded room or recognizing the sound of a babbling brook in a forest. The human brain detects statistical regularities in sounds as a fundamental aspect of prediction, evidenced by reduced responses to repeated sound patterns and enhanced responses to unexpected sounds. Multiple studies demonstrate that the neuronal responses to regular signals are reduced through adaptation, which can contribute to prediction. However, adaptation alone is not sufficient to account for prediction and studies at cellular and neuronal population levels in animals thus far lend only partial support to existing theories of predictive coding. The goal of the project is to close this gap in knowledge and to determine the circuits that predict signals and detect statistical regularity and its violation in auditory behavior. Funded by NIH NIDCD. (2) Neuronal circuits for learning-driven changes in auditory perception: Everyday auditory behavior depends critically on learning-driven changes in auditory perception that rely on neuronal plasticity within the auditory pathway. By combining state-of-the-art optogenetic, electrophysiological, behavioral and computational approaches, the project seeks to identify the function of specific circuit elements in auditory learning. Funded by NIH NIDCD. (3) Neuronal mechanisms for hearing under uncertainty: In everyday life, because both sensory signals and neuronal responses are noisy, important cognitive tasks, such as auditory categorization, are based on uncertain information. To overcome this limitation, listeners incorporate other types of signals, such as the statistics of sounds over short and long time scales and signals from other sensory modalities into their categorization decision processes. This project will identify the contribution of specific cell types to categorization and the neuronal mechanisms for how contextual signals bias auditory categorization. In collaboration with Dr. Yale Cohen <https://auditoryresearchlaboratory.weebly.com/> and Dr. Konrad Kording <http://kordinglab.com/>, funded by NIH BRAIN Initiative. Our laboratory is a close community of fun-loving scientists, striving to help each other while exploring the mysteries of the brain. Our trainees have won numerous awards and have been awarded government and private foundation grants. We value diversity and promote equity in the scientific community and beyond <https://hosting.med.upenn.edu/hearing/philosophy/>. The systems neuroscience community at the University of Pennsylvania is top-notch and highly collaborative, and postdoctoral fellows will have opportunities to engage in interdepartmental initiatives, including MindCore <https://mindcore.sas.upenn.edu/>, MINS <https://www.med.upenn.edu/ins/> and CNI <https://www.cni.upenn.edu/>. Penn has a gorgeous campus and offers many cultural activities. Philadelphia is a beautiful city with world-class music, food and entertainment. To apply, please email Dr. Geffen at mgeffen(a)pennmedicine.upenn.edu <mailto:mgeffen@pennmedicine.upenn.edu> : a cover letter (summarize your prior research experience, why you are interested in the position, and your future plans) and your CV. __________________________ Maria N. Geffen, Ph.D. (she/her) Associate Professor Department of Otorhinolaryngology Department of Neuroscience Department of Neurology Stemmler Hall G14 3450 Hamilton Walk Philadelphia PA 19104 (215)898-0782 mgeffen(a)pennmedicine.upenn.edu http://hosting.med.upenn.edu/hearing Twitter: @neimarkgeffen

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Three Assistant Professor Positions at University of Sussex
by Thomas Nowotny June 22, 2021

June 22, 2021

Dear all, The School of Engineering and Informatics at the University of Sussex is seeking to hire three Assistant Professors (“Lecturers”, permanent position) in Computer Science and AI. One of the positions is particularly focused on a researcher with interests in one or more of the following areas: machine learning, ethical AI, computational Neuroscience, complexity science, consciousness science and bio-inspired AI and robotic control. They should be able to teach general subjects in Computer Science and Artificial Intelligence at Undergraduate and Taught Postgraduate levels. They will work within the Artificial Intelligence Research Group, including opportunities to interact with the robotics group in the Department of Engineering. The AI Research Group at the University of Sussex was created through the merger of the Evolutionary and Adaptive Systems (EASy) and the Data Science groups. We conduct research and teach a wide range of AI related topics, often cross-disciplinary and with a unique Sussex angle. We collaborate internationally and locally with academics, businesses, and public stakeholders, working at the frontiers of knowledge, on solving real-world problems, and in policy and public outreach. Applications should be accompanied by a full CV, and statements of future research plans and ways in which the applicant could contribute to teaching across the School. Please contact Dr Ian Mackie I.Mackie(a)sussex.ac.uk<mailto:I.Mackie@sussex.ac.uk> , Head of the Department of Informatics, for informal enquiries. The full job advert is posted at https://t.co/K0CdIYx6xH?amp=1 including a detailed person specification and details how to apply. Please get in touch if you are interested in these positions and forward to any interested colleagues. Kind regards, Thomas -- Prof Thomas Nowotny Head of the AI Research Group Director of Research and Knowledge Exchange School of Engineering and Informatics University of Sussex Falmer, Brighton BN1 9QJ, UK Phone: +44-1273-678593 FAX: +44-1273-877873

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Post-doc / research associate position in neural reinforcement learning using causal models (Sheffield, UK, 33 months, deadline 4th July)
by Aditya Gilra June 22, 2021

June 22, 2021

Dear All, We're looking for a post-doc / research associate to work on bio-plausible neural networks that learn causal models of the environment and utilize these to plan and explain actions in reinforcement learning. The position is for 33 months at the University of Sheffield, UK. Read more at: https://www.chistera.eu/projects/causalxrl . Apply via (deadline: 4th July): https://jobs.shef.ac.uk/sap/bc/webdynpro/sap/hrrcf_a_posting_apply?PARAM=cG… Best, Aditya. -- Aditya Gilra, Lecturer (Assistant Professor), Machine Learning Group <https://www.sheffield.ac.uk/dcs/research/groups/machine-learning> & Neuroscience Institute <https://www.sheffield.ac.uk/neuroscience-institute/research/computational-a…> , Department of Computer Science, University of Sheffield, UK. https://www.sheffield.ac.uk/dcs/people/academic/aditya-gilra

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WWNeuRise series on neuromodulation & applications/recommendations
by William Podlaski June 21, 2021

June 21, 2021

WorldWideNeuRise will host several online talks throughout June-July on the topic of neuromodulation in the brain from the following speakers: Wednesday, 30 June, 5pm CET Lindsay Collins (McCormick Lab, University of Oregon, USA) Cristina Colangelo (Blue Brain Project, EPFL, Switzerland) Wednesday, 14 July, 5pm CET Jasmine Pickford (Apps Lab, University of Bristol, UK) Luke Coddington (Dudman Lab, Janelia Research Campus, USA) Wednesday, 28 July, 5pm CET Rohan Sharma (Suhita Lab, IISER Pune, India) Ines Guerreiro (Gutkin Lab, Ecole Normale Superieure, France) For more information, please visit our website (https://neurise.github.io/) find us on WorldWideNeuro (https://www.world-wide.org/Neuro/WWNeuRise/) or follow us on Twitter (https://twitter.com/WWNeuRise) We are actively searching for PhD students and postdocs to give talks in our upcoming seminar blocks. On our website (https://neurise.github.io/) you can find an application form to directly apply, as well as a recommendation form, where you can suggest individuals from your lab, institute, or otherwise who you think might have an interesting story to tell! We are looking forward to seeing you at our upcoming seminars! The organising committee, Ellen Boven (Apps lab, University of Bristol) Christina Buetfering (Häusser lab, University College London) Lucie Descamps (Kentros lab, Norwegian University of Science and Technology) Gily Ginosar (Ulanovsky lab, Weizmann Institute) Loreen Hertäg (Clopath lab, Imperial College London) Joram Keijser (Sprekeler lab, TU Berlin) Bill Podlaski (Machens lab, Champalimaud Research)

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NeuroML hands-on satellite tutorial at CNS*2021 on July 2nd 2021 at 1500 UTC
by Ankur Sinha June 21, 2021

June 21, 2021

Dear all, Apologies for the cross-posts. We will be running a half day satellite tutorial at the 30th annual meeting of the Organization for Computational Neurosciences (OCNS), CNS*2021 Online. The tutorial will be held on July 2nd, 2021 at 1500 UTC. https://docs.neuroml.org/Events/202107-CNS2021.html The goal of the tutorial is to teach users to build, visualise, analyse, and simulate models using NeuroML. Why take part? --------------- This tutorial is aimed at new and current NeuroML users. We will start with a quick introduction to the NeuroML standard and the associated software ecosystem, after which we will proceed to conduct hands-on sessions to show how one can build computational models with NeuroML. Times and dates ---------------- - Friday 2nd July 1500 UTC Click here for your local time: https://www.timeanddate.com/worldclock/fixedtime.html?msg=NeuroML+tutorial+… Registration ------------- To take part in the tutorial, please register here for the CNS*2021 meeting: https://www.cnsorg.org/cns-2021 Pre-requisites --------------- The sessions will make use of the NeuroML Python tools. Please follow the documentation to install them on your system if you wish to use them locally: - PyNeuroML: https://docs.neuroml.org/Userdocs/Software/pyNeuroML.html#pyneuroml - libNeuroML: https://docs.neuroml.org/Userdocs/Software/libNeuroML.html#libneuroml You can also use the interactive Jupyter notebooks from the documentation if you prefer (example: https://docs.neuroml.org/Userdocs/NML2_examples/SingleNeuron.html) These can be run on Binder and Google Collab in your web browser and do not require you to install anything locally on your computer. Slack ----- To aid communication with the community during (and after) the meeting, we have a Slack channel for NeuroML related discussions. Please contact Padraig Gleeson (p DOT gleeson AT ucl DOT ac DOT uk) or Ankur Sinha (ankur DOT sinha AT ucl DOT ac DOT uk) for an invite. You can also contact the NeuroML community using one of our other channels: https://docs.neuroml.org/NeuroMLOrg/CommunicationChannels.html#contact-chat We look forward to working with the community to drive further uptake of NeuroML compliant models and tools! -- Thanks, Regards, Ankur Sinha (He / Him / His) Research Fellow at the Silver Lab | http://silverlab.org/ Department of Neuroscience, Physiology, & Pharmacology University College London, London, UK Time zone: Europe/London

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Q&A about INCF activities and membership
by Helena Ledmyr June 21, 2021

June 21, 2021

Hello! Are you an open neuroscience practitioner or want to become one? Do you want to have input on global strategies for data sharing in neuroscience? Join the INCF network! INCF directors Helena Ledmyr and Mathew Birdsall Abrams will answer all your questions about INCF participation in our webinar on June 29th at 10am EDT / 4pm CEST, where long-time community member Samir Das (McGill U) will reflect on how he has benefited from membership. Register at bit.ly/INCFwebinar Information about INCF and memberships can be found on our website <https://www.incf.org/>. All the best, Helena Ledmyr ----------------------------- Helena Ledmyr, PhD *Director* *Development and Communications* International Neuroinformatics Coordinating Facility Secretariat Karolinska Institutet. Nobels väg 15A, SE-171 77 Stockholm. Sweden Email: helena.ledmyr(a)incf.org Phone: +46 8 524 870 35 incf.org neuroinformatics.incf.org

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Assistant professor position in Göttingen, Germany
by Ecker, Alexander June 21, 2021

June 21, 2021

We have an opening for an assistant professor position for ML/CV for biomedical applications in the computer science department at the University of Göttingen, Germany. Application deadline it July 11. For details see below or at https://www.uni-goettingen.de/en/645470.html The Faculty of Mathematics and Computer Science at the Georg-August-University of Goettingen invites applications for a Sartorius AG Endowed Junior Professorship W1 – „Computational Cell Analytics“ (all genders welcome) The junior professorship will be part of the "CIDAS-Sartorius lab for AI-based high-throughput analysis of cell systems" and will actively contribute to its further development. In the CIDAS-Sartorius Lab, we will develop novel data analysis methods to obtain scientific insights from observations of cell systems in various areas of the life sciences. It is a collaboration between the Campus Institute Data Science (CIDAS), the Institute for Computer Science, the University Medical Center Goettingen and Sartorius AG. The junior professorship will also be part of the Campus Institute Data Science (CIDAS) and contribute to its development. CIDAS is a central institution of the University of Goettingen and works closely with the partners of the Goettingen Campus such as the University Medical Center, several Max Planck Institutes, the German Primate Center, the Academy of Sciences and the German Aerospace Center Goettingen. The junior professorship is thus optimally integrated into Goettingen's top-notch life science research environment. The future holder of the position should have expertise in computer science with a focus on machine learning/deep learning and/or computer vision. The professorship contributes to the development of new analytical methods and their application in the field of cell analysis. Possible research foci are among others: - Computer vision in biomedical imaging - Biomedical image processing - Image based cell and biomolecular analytics - Methods for object recognition and image segmentation - Large-scale machine learning & deep learning - Nonlinear and dynamic prognosis models for the description and prediction of complex, nonlinear processes in cell models The candidate should have a track record of internationally competitive high-quality research and a high potential for groundbreaking research in internationally visible projects. The candidate is expected to contribute to teaching in the data science programs. Goettingen University is committed to research-oriented teaching. Applications of international scientists are highly encouraged. The University is an equal opportunity and family friendly employer. We specifically encourage women to apply. Disabled persons with appropriate qualifications and aptitude for the position will be given special consideration. Applications including CV, publications list and details of teaching and research including funded research projects should be submitted by 11 July 2021 online via the application portal: https://tinyurl.com/44r336yn For further information please contact Prof. Dr. Alexander Ecker, Institute of Computer Science and Campus Institute Data Science: ecker(a)cs.uni-goettingen.de. -- Alexander Ecker Professor of Data Science Department of Computer Science • Campus Institute Data Science University of Göttingen • Max Planck Inst. for Dynamics and Self-Organization Goldschmidtstr. 1 • room 2.137 • 37077 Göttingen https://eckerlab.org • @alxecker • +49 551 39-21272

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PhD Studentship in Improving medication verification for cancer patients
by Shangming Zhou June 20, 2021

June 20, 2021

Dear All, *PhD Studentship in Improving medication verification for cancer patients: An AI driven population health study* Applications are invited for a three-year PhD studentship. The studentship will start on* 1 October, 2021, *or as soon as possible after that. *Overview of the Studentship* This fully funded PhD studentship is based at the University of Plymouth’s Centre for Health Technology <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…>, a leading international research group focused on the design, development and implementation of health technology innovations in health and care. This vibrant team of researchers work within the intersection of digital health, software engineering, data science, clinical artificial intelligence, and innovation strategy, with a primary aim to create a global hub for technology incubation in the South West of the United Kingdom. *Project Description* Medication errors, including those in prescribing, dispensing, or administration of a drug, are the single most preventable cause of patient harm. They have a significant impact on the efficiency of the workflow in pharmacy, raise safety concerns for patients, and result in a financial burden on the healthcare systems. Within cancer treatment, emphasis on reducing the number of medication errors has been an active research area for many years, with understanding that interdisciplinary approaches are vital to assure continuous improvement. Opportunities created by the reduction of transaction times for complex computational processes and use of machine learning to support clinical decision making, create a potential catalyst for the development of tools for reduction in medication errors. This PhD studentship offers an exciting opportunity of exploring AI and machine learning with large clinical data sets residing within electronic health records to create methods to assure the effective use of systemic anticancer treatment (including traditional cytotoxic chemotherapy, immunotherapy, novel oral therapies etc.) without compromising patient safety. The studentship will require application of interdisciplinary skills to enable cooperation between the research, clinical, industry and patient communities in the development of a novel approach which could enhance clinical outcomes. *Supervision Team* - Professor Shang-Ming Zhou <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…> (shangming.zhou(a)plymouth.ac.uk) https://scholar.google.com/citations?user=iWiXGWMAAAAJ&hl <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fscholar.g…> - Dr Edward Meinert (edward.meinert(a)plymouth.ac.uk) https://scholar.google.com/citations?hl=en&user=7V-WsrwAAAAJ <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fscholar.g…> - Mrs Andrea Preston (Andrea.Preston(a)uhbw.nhs.uk) This PhD student will be academically advised by Professor Shang-Ming Zhou and Dr Edward Meinert, research scientists with research interests in applied artificial intelligence and machine learning, computing science in health and care. The student will also be advised by Mrs Andrea Preston, a Macmillan Divisional Lead Haematology & SW Cancer Commissioning Pharmacist. This supervision team will assure the execution of a world-class PhD embedded into the wider digital health ecosystem at the University of Plymouth. *Eligibility* · This PhD studentship is offered for UK and international applicants. · Applicants should have: 1) A first or upper second-class honours degree, and a relevant Master’s qualification in Computing Science, Data Science, Statistics, Health Informatics, Medical Informatics, Bioinformatics, or any areas related; 2) Interest in working with real-world problems and large data sets; 3) Excellent proficiency in English and outstanding communication skills; 4) Strong analytical and programming skills; 5) A “can do”, positive attitude with an aspiration to change the world. · Experience in machine learning is advantageous. · Experience in publication of peer-reviewed literature is desirable. *International Students* International applicants should meet the English language requirements, please see the details from the University’s website https://www.plymouth.ac.uk/international/how-to-apply/english-language-requ… <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…>. IELTS Academic 6.5 or above (or equivalent) with 5.5 in each individual category is commonly required by the University’s Doctoral College. *How to Apply* *To apply for this position,* please visit: https://www.plymouth.ac.uk/student-life/your-studies/research-degrees/postg… <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…>. *Please clearly state the name of the studentship that you are applying for on your Personal Statement.* A research proposal is required. Please see: https://www.plymouth.ac.uk/student-life/your-studies/research-degrees/appli… <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…> for a list of supporting documents to upload with your application. *Enquiry * If you wish to discuss this project further informally, please contact Professor Shang-Ming Zhou (shangming.zhou(a)plymouth.ac.uk) Dr Edward Meinert (edward.meinert(a)plymouth.ac.uk) or Mrs Andrea Preston ( Andrea.Preston(a)uhbw.nhs.uk) For more information on the admissions process, please contact doctoralcollege(a)plymouth.ac.uk. *Closing Date* *The closing date for applications is 30 July 2021. *Shortlisted candidates will be invited for interview. Best wishes Shangming Zhou _______________________________________________________ Shang-Ming Zhou Professor in e-Health, Fellow of the Higher Education Academy, Centre for Health Technology, Faculty of Health, University of Plymouth, Plymouth, PL4 8AA, UK Tel: +44 (0)1752 586513 Email: shangming.zhou(a)plymouth.ac.uk ; smzhou(a)ieee.org https://www.plymouth.ac.uk/staff/shang-ming-zhou <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…> https://www.hdruk.ac.uk/people/dr-shang-ming-zhou <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.hdruk…> https://www.plymouth.ac.uk/research/centre-for-health-technology <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…>

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BrainCosmos Summer School on Neural Circuit Complexity from Aug 30-Sep 3
by Shyam Diwakar June 19, 2021

June 19, 2021

Dear Fellow Neuroscientists and Students, We would like to welcome you to a BrainCosmos Summer School titled "Neural circuit complexity: Neuroscience, Models and Robotics - Where do they lead?" organized at Lake Como, Italy from August 30-September 3, 2021. For more info: https://brco.lakecomoschool.org/ <https://brco.lakecomoschool.org/> The BrainCosmos summer school focuses on the study of the brain, neuroscience of circuits and behavior in micro and macro scales, models, experiments, alongside topics of robotics and artificial intelligence and a perspective on brain diseases. The school primarily targets PhD students across all research disciplines, but applications from professionals, masters students and post-doctoral researchers are welcome as well. The School will also cater to early career researchers in Neuroscience and will aim to promote critical thinking within the field and beyond. The scope covers a very wide range of topics that we believe to be of interest to many fields related to neuroscience, modeling, robotics and artificial intelligence. PARTICIPATION: The school will run in parallel with two simultaneous batches, one in presence (20 participants) and another remotely (20 participants). The lectures will be streamed. APPLY: https://brco.lakecomoschool.org/application/ FEES: There are some nominal fees for participation. In presence attendance: € 120, 22% VAT included (including lunches, coffee breaks, and all lectures and school materials). Online attendance: €100, 22% VAT included (including the possibility to participate remotely to all the lectures given during the school and to the related initiatives, and to have access to the recordings of the lessons from the school portal for a period of three months after the end of the school. KEY DATES Application deadline: July 20 Acceptance notification: July 23 Registration (only accepted students): August 3 Confirmed FACULTY list: Anna Letizia Allegra Mascaro - LENS, Florence, Italy Alberto Antonietti - EPFL, Swiss Silvia Casarotto – University of Milan, Italy Claudia Casellato - University of Pavia, Italy Marco Dal Maschio – University of Padoa, Italy Egidio D'Angelo - University of Pavia, Italy Damien Depannemaecker - CNRS, Paris, France Shyam Diwakar - Amrita Mind Brain Center, Amrita University, India Kenji Doya – Okinawa Institute of Science and Technology Graduate University, Japan Claudia Gandini Wheeler-Kingshott - University College London, UK & University of Pavia, Italy Alice Geminiani - University of Pavia, Italy Michele Giugliano – SISSA, Trieste, Italy Alberto Mazzoni - Scuola Superiore Sant’Anna Pisa, Italy Michele Migliore - CNR Palermo, Italy Fulvia Palesi – BCC Pavia, Italy Alessandra Laura Giulia Pedrocchi - Politecnico Milano, Italy Michele Piana - University of Genoa, Italy Isabella Pozzi - CWI, Amsterdam Holland Simone Sarasso – University of Milan, Italy The School DIRECTORS: Giovanni Naldi - University of Milan, Department of Environmental Science and Policy, Italy. giovanni.naldi(a)unimi.it<mailto:giovanni.naldi@unimi.it> Thierry Nieus - University of Milan, Italy. thierry.nieus(a)unimi.it<mailto:thierry.nieus@unimi.it> Simone Sarasso - University of Milan, Department of Biomedical and Clinical Sciences “Luigi Sacco”, Italy. simone.sarasso(a)unimi.it<mailto:simone.sarasso@unimi.it> Shyam Diwakar - Amrita Mind Brain Center, Amrita University, India. shyam(a)amrita.edu<mailto:shyam@amrita.edu> Please feel free to circulate! With best wishes, -- Prof. Shyam Diwakar, Ph.D. Director - Amrita Mind Brain Center Faculty Fellow - Amrita Center for International Programs Amrita Vishwa Vidyapeetham (Amrita University) Amritapuri, Clappana P.O. Kollam, India. Pin: 690525 Ph:+91-476-2803116 Fax:+91-476-2899722 http://amrita.edu/mindbrain [https://docs.google.com/uc?export=download&id=1_nOxaCXob6wVcuQyYI5KVk1PhMgi…] [https://intranet.cb.amrita.edu/sig/RankingLogo.png] Disclaimer : The information transmitted in this email, including attachments, is intended only for the person(s) or entity to which it is addressed and may contain confidential and/or privileged material. Any review, retransmission, dissemination or other use of, or taking of any action in reliance upon this information by persons or entities other than the intended recipient is prohibited. Any views expressed in any message are those of the individual sender and may not necessarily reflect the views of Amrita Vishwa Vidyapeetham. If you received this in error, please contact the sender and destroy any copies of this information.

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Job: Editor with Nature Machine Intelligence (9 month locum position - London, NY, Berlin)
by Yann Sweeney June 18, 2021

June 18, 2021

Dear all, Nature Machine Intelligence are looking to recruit a locum editor. We are a new Nature Research journal that launched in 2019. It publishes both fundamental and applied research in a wide range of areas in artificial intelligence and robotics. The journal incorporates elements of computer science, electrical engineering, mathematics, physics, neuroscience, cognitive science and psychology. The journal also publishes news, commentary and perspectives on the impact of machine intelligence on science and society. We are inviting applications from those with a background in any of the above and related fields. Applicants should have completed a PhD, have a strong research record, feel driven to continually learn about new fields and trends and have a keen interest in exploring the wide implications of research on other scientific areas, industry and society. We would be interested in hearing from candidates who can demonstrate strong science writing skills. Editorial experience is not required, although applicants with significant editorial experience are encouraged to apply and will potentially be considered for a Senior Editor position. The successful candidate will report to the Chief Editor. They will participate in all aspects of the editorial process, including manuscript selection, commissioning and editing News and Views, Comments, Perspectives and Reviews, as well as writing for the journal. The successful candidate must be dynamic and outgoing, and have excellent communication and interpersonal skills. A key aspect of the job is liaising with the research community through laboratory visits and international conferences, and therefore a willingness to travel is essential. The position is offered on a full-time basis, for an initial fixed term of 9 months, and will ideally be located in our London, Berlin or New York office. The starting date is envisaged as soon as possible within the next few weeks. Full advert here, apply by 22 June: https://career5.successfactors.eu/sfcareer/jobreqcareer?jobId=33925&company… Feel free to email with informal inquiries. All the best, Yann Senior Editor Nature Machine Intelligence yann.sweeney(a)nature.com

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