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Postdoctoral fellowships at the Neuromathematics Center in Sao Paulo State, Brazil
by Antonio Roque April 24, 2019

April 24, 2019

Positions for Postdoctoral Researchers The Research, Innovation and Dissemination Center for Neuromathematics ( NeuroMat <https://neuromat.numec.prp.usp.br/>), hosted by the University of Sao Paulo, Brazil, and funded by the Sao Paulo Research Foundation (FAPESP <http://www.fapesp.br/en/>), is offering several postdoctoral fellowships for recent PhDs with outstanding research potential. The research will involve collaborations with experimental and theoretical groups and laboratories associated to NeuroMat. The research to be developed by the postdoc fellows shall be strictly related to ongoing research lines developed by the NeuroMat team. The project may be developed at USP Sao Paulo, USP Ribeirao Preto or Unicamp. We seek candidates capable to develop independent research in one of the research lines below. 1. Stochastic and/or computational modeling of the brain functioning. 2. Acquisition, processing and quantitative analysis of electrophysiological data. 3. Biomedical devices for neuroscience research. Candidates to the first research line are required to have at least one of the profiles below: · A strong background in probability theory with emphasis on stochastic processes. Previous knowledge of rigorous statistical mechanics or random graphs will be favorably considered. · A strong mathematical and/or computational background and experience with computers and programming. Previous experience with development and/or simulation of neural brain models, complex networks and parallel computing will be favorably considered. Candidates to the second research line are required to have at least one of the profiles below: · A strong background in neuroscience with previous experience in neurophysiological data acquisition, processing and analysis, and knowledge of computer programming. · A strong background in computer science with experience in the development of algorithms, software tools and data bases. Previous research experience in neuroscience or related areas will be favorably considered. Candidates to the third research line are required to have at least one of the profiles below: · A strong background in electromagnetism and biomedical engineering. Previous knowledge of transcranial magnetic stimulation or magnetic/electric field simulation will be favorably considered. · A strong background in computer science and control software development expertise. Previous experience with neuroscience and neuronavigation systems will be favorably considered. Previous experience with multidisciplinary research teams is welcome for all the above research lines. The initial appointment is for one year, with a possible extension to up to four years, conditional on research progress. The fellowship is competitive at international level, and fellows benefit from extra funds for travel and research expenses plus limited support for relocation expenses. Application Instructions Applicants should complete and submit the application form <https://neuromat.numec.prp.usp.br/postdoc/new>. The following documents and information are requested (please see the form for further details): · Summary of the CV, in the FAPESP format (see www.fapesp.br/en/6351 for instructions.) · List of publications, with links to those available online. · A summary of the research plan for the next year, up to 5 pages length. It should explicitly state for which of the three above profiles the candidate is applying. It should also address its place within the framework of the NeuroMat research program <https://neuromat.numec.prp.usp.br/scientific-project>. · Pointers to other research related output, such as software, web pages, and so forth. Candidates should be willing to send copies of publications, if requested. · Any further information deemed relevant to the application. In addition to the above, we require at least 2 recommendation letters. Those should be mailed by the recommenders directly to postdoc-appl(a)numec.prp.usp.br. Candidates are encouraged to apply at their earliest convenience until June 3rd, 2019. Appointments are expected to start by September 1st, 2019. The initial period of the position lasts for 12 months, with possible renovations for up to four years. This opportunity is open to candidates of any nationality. The selected candidates will be awarded FAPESP Post-Doctoral fellowships in the amount of BRL 7,372.40 monthly and a research contingency fund, equivalent to 15% of the annual value of the fellowship, which should be spent in items directly related to the research activity. More information about the fellowship is at: www.fapesp.br/en/5427. -- Dr. Antonio C. Roque Professor Associado Departamento de Fisica FFCLRP, Universidade de Sao Paulo 14040-901 Ribeirao Preto-SP Brazil - Brasil E-mails: antonior(a)usp.br <antonior(a)ffclrp.usp.br> aroquesilva(a)gmail.com URL: www.sisne.org Tels: +55 16 3315-3768 <+55%2016%203315-3768> (sala/office); +55 16 3315-3859 <+55%2016%203315-3859> (lab) FAX: +55 16 3315-4887 <+55%2016%203315-4887>

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Post-doc @ Univ of Toronto: bioinformatics, neuron modeling, and machine learning
by Shreejoy Tripathy April 24, 2019

April 24, 2019

Post-doctoral fellowship in multi-scale bioinformatics and neuroscience – Tripathy laboratory, CAMH, University of Toronto Job Description: We are looking for a post-doctoral fellow with a background in bioinformatics, computational biology, or neuroinformatics. The position is in the Laboratory for Computational Genomics, under the supervision of Dr. Shreejoy Tripathy (https://triplab.org/) . The post-doc will contribute to a growing team at the new Krembil Centre for Neuroinformatics, based at CAMH and the University of Toronto. Project Description: The candidate will lead a multi-disciplinary dry-lab project in multi-omics and cellular neuroscience. The project’s goal is to identify cross-modal relationships between: 1) human genotypes; 2) tissue- and cell type-specific gene expression; and 3) neuronal and circuit phenotypes, including electrophysiology, morphology, and synaptic physiology. The candidate will develop and apply machine learning and statistical methods to translate information across these data types. The project will make use of publicly-accessible datasets (e.g., PGC, PsychEncode, Allen Institute) as well as private datasets provided by collaborators. The post-doc will interface with a team of experimentalists and computational modelers to directly test their predictions and work with clinician-scientists to use these approaches for patient stratification. The ideal candidate is someone who is passionate about using basic research in genomics and neuroscience to improve the understanding and treatment of psychiatric disorders. Position details: The position is for a duration of up to 3 years, renewed yearly. Compensation, including benefits, is competitive and will be based on experience and established pay-scales. The candidate will support a healthy workplace that embraces diversity, encourages teamwork, and complies with all applicable and regulatory requirements. Qualifications: A recent PhD in bioinformatics, neuroscience, or statistics (or equivalent computational discipline) Considerable experience programming, scripting, and analyzing data in a high-level language (e.g., R, Python, or MATLAB) Experience analyzing and quality-controlling multi-omics datasets, including genotyping, transcriptomics, and cellular characteristics A track record for independent research that demonstrates creativity Excellent communication skills and experience working in a collaborative and multi-disciplinary environment How to apply: A complete application should include a brief cover letter, a curriculum vitae, and the contact information for 2-3 references. Submit applications to Shreejoy Tripathy (shreejoy.tripathy(a)utoronto.ca) with the title: “Post-doc in multi-scale bioinformatics and neuroscience” in the subject line. In the cover letter, please highlight one or two publications or preprints the candidate feels is their best work. Applications will be reviewed in an ongoing manner and the position will remain open until filled. About the Krembil Centre for Neuroinformatics: In 2017, Centre for Addiction and Mental Health (CAMH) established its new $15-million Krembil Centre for Neuroinformatics to leverage the largest mental health patient database in Canada and combine world-leading talent specializing in computational approaches to brain science, a robust data integration platform, and analytical tools to accelerate and revolutionize the world’s understanding of the brain and brain-based illnesses. The Krembil Centre for Neuroinformatics positions CAMH as a leader in brain science using the power of big data analytics, artificial intelligence and machine learning, and multi-scale brain modelling in order to bridge the levels of the structure and function of the brain – from genes to circuits to behavior.

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Tenure Track Faculty Position - Systems and Computational Biology
by Ruben Coen-Cagli April 24, 2019

April 24, 2019

Dear colleagues, our department is recruiting faculty with an emphasis on theoretical, computational and experimental approaches to studying complex biological systems, including computational neuroscience. Details in the ad below. The Albert Einstein College of Medicine, one of the leading medical schools, located in New York City, is seeking to fill multiple tenure track faculty positions in the Department of Systems and Computational Biology. The major goal of the department is to advance our understanding of living systems by developing theoretical, computational and experimental approaches to study complex biological systems. The College has 711 medical students, 160 Ph.D. students and 107 M.D./Ph.D. students, 265 postdoctoral research fellows in training and boasts a strong research faculty covering broad areas of experimental biology. The College of Medicine has more than 1,800 full-time faculty members located on the main campus and at its clinical affiliates. The 200,000 square foot Center for Genetic and Translational Medicine at Einstein locates computational, systems and experimental scientists in physical proximity to foster interdisciplinary communication and collaboration. Highly competitive start-up packages are available. [https://analytics.click2apply.net/v/Y7MBopTB6AyKtRmRu8Xgz] We seek outstanding scientists with broad experience and demonstrated collaborative interactions with experimental or clinical investigators. Candidates should have strength in a physical, mathematical or computational field at the Ph.D. or equivalent level. Experience applying these skills to a biological or biomedical area (demonstrated through publications or support) is also desirable. Areas of interest include, but are not limited to: Modeling cellular processes; Evolutionary medicine; Evolution of structure and function; Biological networks analysis; Microbiome; Computational neuroscience; Mathematical and computational modeling of high-dimensional data related to complex traits. Applicants should send a letter of interest, C.V., statement of research and teaching interests, and names of three referees, in electronic format to: Systems and Computational Biology Search Committee Albert Einstein College of Medicine Jack and Pearl Resnick Campus 1300 Morris Park Ave. Price Center, Rm. 153 Bronx, New York 10461 E-mail Address: SysBio(a)einstein.yu.edu<mailto:SysBio@einstein.yu.edu> Subject line should be: SCB Faculty Search The Albert Einstein College of Medicine is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information. Ruben Coen Cagli, PhD Department of Systems and Computational Biology, and Dominick Purpura Department of Neuroscience Albert Einstein College of Medicine 1300 Morris Park Ave. Price 353B Bronx, 10461. NY office: +1.718.678.1150 web: https://sites.google.com/site/rubencoencagli/

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postdoctoral positions in computational neuroscience at IIT, Italy
by Stefano Panzeri April 24, 2019

April 24, 2019

Two postdoctoral positions will be available at Istituto Italiano di Tecnologia) to work with me (Stefano Panzeri https://www.iit.it/people/stefano-panzeri) in the laboratory of Neural Computation. The laboratory investigates, by developing and using advanced data analysis methods and neural network models, how circuits of neurons in the brain encode information and use it to produce appropriate behaviors. The positions on offer would leave the candidate the choice of developing a research project of mutual interest within this research area. The laboratory offers a wide range of interdisciplinary expertise in computational neuroscience, including both advanced neural analysis techniques and neural network modeling. The laboratory also offers a thriving, ambitious research environment which is well funded (including several grants from the NIH Brain Initiative). Moreover, the laboratory offers extensive long-term international collaborations with empirical neuroscience laboratories (including Chris Harvey at Harvard Medical School, Wei Lee at Children’s Hospital, Christoph Kayser at Bielefeld, Nikos Logothetis at Tuebingen, Mathew Diamond at SISSA, Tommaso Fellin and Cristina Becchio at the IIT, Alex Thiele at Newcastle) and ample opportunities for advanced training and personal scientific growth. I seek candidates holding a PhD in a numerate or neuroscientific discipline, with a solid computational background and a keen interest in neuroscience. They must be highly motivated and creative individuals who want to work in a dynamic, multi-disciplinary research environment and be willing to interact with both experimental and theoretical neuroscientists. The successful candidate will have the opportunity to conduct research at the IIT center in Rovereto (Italy), or at the IIT headquarters in Genova, (Italy). For representative recent publications from my lab, please see: Runyan C. A., et al (2017) Distinct timescales of population coding across cortex, Nature: 548: 92-96. Panzeri S., et al (2017) Cracking the neural code for sensory perception by combining statistics, intervention and behaviour. Neuron 93: 491-507 Safaai, H., et al (2015) Modelling the effect of Locus Coeruleous firing on single trial cortical state dynamics and sensory processing. Proc. Natl. Acad. Sci. USA 112(41): 12834–12839 Further information about my research can be found at my IIT and Google Scholar web pages: https://www.iit.it/people/stefano-panzeri https://scholar.google.it/citations?user=C-HCQ9cAAAAJ&hl=en Applications (full CV, statement of research interest and name and contact of 2 referees) should be sent by e-mail to stefano.panzeri(a)iit.it, quoting “Postdoctoral position in Computational Neuroscience” in the subject line. The deadline for applications is May 18th, 2019. Applications will be examined until the position is filled. Interested applicants are advised to contact me by email informally as soon as possible to discuss about the science and the position informally. Thanks Stefano Panzeri

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First Call for Papers: Neurodegeneration and Language - Special Session on Language Disorders
by Dimitrios Kokkinakis April 24, 2019

April 24, 2019

*Call for Papers [apologies for x-posting]* *Neurodegeneration and Language - Special Session on Language Disorders* *Special session date*: September 27th, 2019 Lisbon, Portugal, co-located with ExLing-2019 *Website*: https://spraakbanken.gu.se/eng/neural-2019 *Submissions*: https://exlingworkshop.com/exling-2019/special-sessions-2019.html *Deadline of extended abstract submission**: *July 1st, 2019 *Contact**:* dimitrios _DOT_ kokkinakis _AT_ gu _DOT_ se *NEURodegeneration And Language (NEURAL 2019)* is a special session on language disorders which will take place in the context of *ExLing 2019 <https://www.exlingworkshop.com/>* in Lisbon, Portugal, 27 September 2019, under the auspices of *Centro de Linguística da Universidade de Lisboa.* The *NEURAL 2019* special session aims to advance our knowledge on language disorders and the development of experimental methods for the analysis and processing of speech and language. Special emphasis is put on interdisciplinary approaches among different research areas, including computational linguistics (CL), (cognitively inspired) natural language processing (NLP), speech acoustics, and also other related areas and modalities, including wearable, vision, and ambient sensor technologies . The special session programme will contain a combination of oral and poster papers on main areas of language disorders. Furthermore, attendees will have opportunities of free discussions among *NEURAL 2019* as well as *ExLing 2019 <https://www.exlingworkshop.com/>* participants. Submission of 4-page papers related to the above aims of the special session *NEURAL 2019* are welcome at <https://www.exlingworkshop.com/exling-2019/submissions-2019.html> https://www.exlingworkshop.com/exling-2019/special-sessions-2019.html

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DeepMath 2019 Call for Contributions
by Ahmed El Hady April 21, 2019

April 21, 2019

*ANNOUNCEMENT AND CALL FOR CONTRIBUTIONS* ** * The 2019 Conference on Mathematical Theory of Deep Neural Networks (DeepMath 2019) Princeton Club, New York City, Oct 31-Nov 1 2019. Web: https://www.deepmath-conference.com/ ======= Important Dates ======= Submission deadline for 1-page abstracts: June 28, 2019 Notification: TBA. Conference: Oct 31-Nov 1 2019. ======= Confirmed speakers ======= Anima Anandkumar (CalTech), Yasaman Bahri (Google), Minmin Chen (Google), Michael Elad (Technion), Surya Ganguli (Stanford), Tomaso Poggio (MIT), David Schwab (CUNY), Shai Shalev-Shwartz (Hebrew University), Haim Sompolinsky (Hebrew University and Harvard), and Naftali Tishby (Hebrew University). ======= Workshop topic ======= Recent advances in deep neural networks (DNNs), combined with open, easily-accessible implementations, have made DNNs a powerful, versatile method used widely in both machine learning and neuroscience. These advances in practical results, however, have far outpaced a formal understanding of these networks and their training. Recently, long-past-due theoretical results have begun to emerge, shedding light on the properties of large, adaptive, distributed learning architectures. Following the success of the 2018 IAS-Princeton joint symposium on the same topic (https://sites.google.com/site/princetondeepmath/home) the 2019 meeting is more centrally located and broader in scope, but remains focused on rigorous theoretical understanding of deep neural networks. ======= Call for abstracts ======= In addition to these high-profile invited speakers, we invite 1-page non-archival abstract submissions. Abstracts will be reviewed double-blind and presented as posters. To complement the wealth of conferences focused on applications, all submissions for DeepMath 2019 must target theoretical and mechanistic understanding of the underlying properties of neural networks. Insights may come from any discipline and we encourage submissions from researchers working in computer science, engineering, mathematics, neuroscience, physics, psychology, statistics, or related fields. Topics may address any area of deep learning theory, including architectures, computation, expressivity, generalization, optimization, representations, and may apply to any or all network types including fully connected, recurrent, convolutional, randomly connected, or other network topologies. Committee Information: Organizing committee: * Ahmed El Hady * Adam Charles * Mikio Aoi * Andrew Saxe * Joan Bruna * Michael Shvartsman * Sebastian Musslick * Stephen Keeley Advisory committee * Jonathan Cohen * Daniel Lee * Sebastian Seung * Ted Willke Local Committee * NYU: Joan Bruna * Columbia: Ashok Kumar * SUNY Stonybrook: Il Memming Park * Yale: Gal Mishne * City College: David Schwab * IAS: Nadav Cohen *

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Summer School in Computational and Theoretical Models in Neuroscience, Venice, Italy (September 9th - September 14th, 2019)
by Samir Suweis April 19, 2019

April 19, 2019

ConTaMiNEURO 2019 Summer school ,Venice, Italy (September 9th - September 14th, 2019) I would like to bring to your attention to the Summer School in Computational and Theoretical Models in Neuroscience, ConTaMiNEURO 2019 <http://neuroschool19.liphlab.com/> Approaches and techniques from Physics, Mathematics and Computational Science are increasingly becoming critical for understanding and modelling the brain, and also for designing and interpreting experiments. Modeling is an essential tool to cut through the vast complexity of neurobiological systems and their many interacting elements. ConTaMiNEURO 2019 <http://neuroschool19.liphlab.com/> wants to convey central ideas, methods, and practices of modern computational neuroscience through a combination of lectures, tutorials and seminars. During the course’s mornings, distinguished international faculty deliver lectures and seminars on selected topics in computational neuroscience (see below). For the remainder of the time, students work on research projects in teams of 3-4 people under close supervision of expert tutors and faculty. Research projects will include data analyses and the development of theories to explain experimental observations. The School is will take place from 9 to 14 September at palazzo Morelli of the University Ca’Foscari, in the heart of Venice. All the details can be found at the school website: http://neuroschool19.liphlab.com/ <http://neuroschool19.liphlab.com/> Thanks to the support of our sponsor, in particular the University of Padova and the newborn Padova Neuroscience Center (PNC <http://pnc.unipd.it/>), the early bird registration fee for Ph.Ds students and Post Docs is 200 Euro, deadline is 30 June 2019. MAX 40 participants. ConTaMiNEURO 2019 <http://neuroschool19.liphlab.com/> is co-organized by Samir Suweis, Amos Maritan, Maurizio Corbetta, Marco Formentin, Stefano Vassanelli (University of Padova), Achille Giacometti (University of Venice) and Miguel A. Munoz (University of Granada). Invited Speakers Ken Miller, Columbia University, USA. Yiota Poirazi, IMBB-FORTH, Creta. Nicolas Brunel*, Duke University, USA. Andrea Brovelli, University of Marsille. Jordi Soriano, University of Barcellona Mazzuccato Luca, Columbia University & University of Oregon Stefano Panzeri, IIT Rovereto Jesus Cortes, IKERBASQUE: The Basque Foundation for Science Lucilla De Arcangelis, University of Naples Raffaella Burioni, University of Parma Gustavo Deco, Pompeu Fabra University, Barcelona Jonathan Touboul, Brandeis University (USA) Susanne Ditlevsen, University of Copenaghen Alessandro Treves, Trieste SISSA Misha Tsodyks, Weizmann Institute of Science Marco Zorzi, University of Padova Lamberto Ballan, University of Padova Eleni Vasilaki, University of Shieffield Marcello Pelillo, European Center of Living Techonology & University of Venice Tommaso Fellin, IIT Genova Maria Victoria Sánchez Vives , ICREA-IDIBAPS (Barcelona) Marco dal Maschio, University of Padova Serena del Santo, University of Granada Lorenzo Fontolan, Janelia Farm Samir Suweis, Ph.D. ***** LIPh Lab, Physics & Astronomy Dept. University of Padova Tel: +39 049 827 71 74 @SamirSuweis

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Postdoc in large-scale brain modeling and machine learning
by Jan Fousek April 18, 2019

April 18, 2019

A postdoc position is available at the Institut de Neurosciences des Systèmes (http://ins-amu.fr/) Aix-Marseille University, France. Summary The Theoretical Neuroscience Group (Head: Viktor Jirsa) is seeking to fill a post-doctoral position in the context of the project Virtual Brain Cloud to work on development of parameter inference workflows for connectome-based large-scale brain network models (see The Virtual Brain http://www.thevirtualbrain.org) applied to brain imaging data (EEG, MEG, fMRI). In particular, the project will involve the application and evaluation of common Bayesian estimation techniques such as Markov-Chain Monte-Carlo and variational schemes to high-dimensional time-series models of brain activity. These were previously successfully applied in the context of estimation of brain excitability based on personalized brain models and intracerebral electrophysiological recordings of seizure propagation in epileptic patients. The successful candidate will join a team working towards generalizing these approaches for other paradigms such as stimulation or resting state. Qualification Candidates should be have strong background in data fitting (Bayesian inference approaches, Dynamical Causal Modeling (DCM), Monte Carlo techniques). Experience with computational neuroscience (networks, dynamic system theory) and ability to program in a numerically oriented language (R, Python, MATLAB) are valued. The Theoretical Neuroscience Group We are a multi-national team interested in understanding the mechanisms underlying the spatiotemporal organization of large-scale brain networks. Our work comprises mathematical and computational modeling of large-scale network dynamics and human brain imaging data, the development of neuroinformatics tools for studying large-scale brain networks applied to concrete functions, dysfunctions (epilepsy, dementia) and aging. Terms of salary and employment The position is initially for one year, renewable on an annual basis based on performance. Salary will depend on diploma and experience. Operating language in the laboratory is English and French. CONTACT viktor.jirsa(a)univ-amu.fr | Institut de Neurosciences des Systèmes https://ins-amu.fr/ -- Jan Fousek INS - Institut de Neurosciences des Systèmes UMR INSERM 1106, Aix-Marseille Université 27 Bd Jean Moulin, 13005 Marseille https://ins-amu.fr/

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PhD position - Inverse Reinforcement Learning
by Constantin Rothkopf April 18, 2019

April 18, 2019

The Centre for Cognitive Science at Technische Universitaet Darmstadt, Germany invites applications for a Ph.D. Position in Inverse Reinforcement Learning initially limited to a period of three years. Research area The Ph.D. student is expected to work in the domain of inverse reinforcement learning with the particular focus of elucidating human decision making and collective human decision making in the wild, i.e., under real world noisy conditions. The research project is a joint venture between the Bioinspired Communication Lab and the Psychology of Information Processing Lab, both members of the Centre of Cognitive Science at TU Darmstadt. Accordingly, the student will be advised by Prof. Heinz Koeppl, Department of Electrical Engineering and Prof. Constantin Rothkopf, Department of Psychology. Work will involve methodological research in machine learning, design of dedicated human behavioral experiments, and the analysis and further processing of gathered data. What we offer We offer a unique interdisciplinary environment to perform cutting-edge research at one of Germany’s leading universities in the domain of computer science and engineering. The student will be embedded in the ongoing research activities within the Centre for Cognitive Science and will hence have the opportunity to interact with many other cognitive science researchers. The conducted research is expected to culminate in a Ph.D. degree. We offer comprehensive support for dissemination of results through leading scientific journals and through participation in leading international conferences and workshops. Your profile Candidates should have a M.Sc. degree in one of the following fields: computer science, physics, mathematics, engineering, or cognitive science. Candidates are required to have a sincere interest in interdisciplinary research at the crossroad of psychology and computer science. Application We look forward to receiving your application, consisting of a cover letter in which you lay out your interest in the indicated research area, curriculum vitae, copies of certificates and contact details of at least two academic references. Please send your application package as a single PDF file to application(a)bcs.tu-darmstadt.de. Code No. 590. The position is initially advertised till May 3rd 2019, but later applications will be considered until the position is filled. -- Constantin A. Rothkopf, PhD http://www.pip.tu-darmstadt.de/ http://www.cogsci.tu-darmstadt.de/ http://www.ai-da.tu-darmstadt.de/

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Postdoctoral position in multivariate connectivity and computational modeling in fMRI
by Joshua Hartshorne April 18, 2019

April 18, 2019

Second Call. Wanted: Post-doctoral fellow interested in delving into new computational techniques for fMRI analysis. This position is ideal for students with a background in neuroimaging who want to strengthen their technical skills in preparation for a job market that increasingly values advanced analysis methods, or for students with a background in machine learning who want to branch into neuroscience. This Simons Foundation-funded research project will be focused on developing, evaluating, and deploying state-of-the-art multivariate connectivity techniques and other modeling approaches. The initial application will be to a large Autism dataset, and may grow from there depending on progress. The postdoc will work closely with the PIs: Prof. Stefano Anzellotti and Prof. Joshua Hartshorne (Department of Psychology, Boston College). Both PIs run young, small labs, so the post-doc can expect individualized attention and training. Boston College is a research university classified as "Very High Research Activity (R1)" by the Carnegie Classification, and has a bustling Psychology and Neuroscience department with 19 faculty. Graduate students and post-docs in the department regularly go on to prestigious academic appointments (e.g., see https://bit.ly/2PdvK3N) You can learn more about Drs. Anzellotti and Hartshorne at sccnlab.bc.edu and l3atbc.org, respectively. Preferred start date is between June 1 2019 and Jan. 1 2020. Boston College is an Equal Opportunity Employer. Candidates from backgrounds underrepresented in psychology/neuroscience are particularly encouraged to apply. The position is funded for two years and may be renewable beyond the second year depending on funding. Salary follows the NIH Postdoc scale. Boston College is an Equal Opportunity Employer. Candidates from backgrounds underrepresented in psychology/neuroscience are particular encouraged to apply. To apply, submit a CV, contact information for 2-3 references, and a cover letter highlighting relevant research experiences and interests directly to jkhartshorne(a)gmail.com. Review of application is ongoing and will continue until the position is filled.

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