- Comp-neuro - lists.cnsorg.org

Post-doc Postion at Computational Neuroscience Division (ULPGC)

by Carmen Paz Suárez Araujo

Dear colleagues, I’m writing you to share an opportunity for obtaining a postdoctoral position The Marie Curie Chair in Computational Neuroscience at the Institute of Cybernetics, Enterprise and Society (Universidad de Las Palmas de Gran Canaria), led by Prof. Carmen Paz Suárez Araujo, is inviting applications for a postdoctoral position. This is a one-and-a-half-year, non-tenure-track position. Duties will involve research and supervision activities in the following areas: 1) neuro-AI; 2) determination of new functional biomarkers for Alzheimer's disease (AD) and other cortical dementias; and 3) intelligent decision systems for the diagnosis and prognosis of AD. The Marie Curie Chair is seeking outstanding candidates who have received a PhD in Computer Engineering, Electronic and Telecommunications Engineering, Biomedical Engineering, Bioengineering, Physics, or a related discipline. Titles obtained outside of Spain require validation or homologation certificates. Salary: €2,218.52 per month. The probable start date is 1 April 2026. Candidates will be graded on their merits up to a maximum of 10 points (3.5 for professional experience, 3.5 for scientific merits, 1.5 for additional knowledge and experience, and 1.5 for language proficiency). Certificates to justify these merits are mandatory. A job interview will be held with the three candidates who are ranked highest. To apply, please visit https://fpctserver.upe.ulpgc.es/convocatorias/index.php?lang=es Best Regards Prof. Carmen Paz Suárez Araujo

Feb. 17, 2026

Applications Open: BAMB! 2026, Barcelona Summer School for Advanced Modeling of Behavior

by manuel molano

Dear colleagues, We are pleased to announce that applications are now open for the 6th edition of the Barcelona Summer School for Advanced Modeling of Behavior (BAMB! 2026). * Dates: July 12–23, 2026 * Location: Barcelona, Spain * Application Deadline: 6 March 2026 (midnight Pacific Time) * Apply at: www.bambschool.org BAMB! is an intensive two-week training program for PhD students and early-career researchers in cognitive science, computational neuroscience, and Neuro-AI who possess a strong computational background. For this new edition, we have reformulated the curriculum to address the rapid transformations currently occurring in computational neuroscience, ensuring the course remains at the cutting edge of advanced modeling. The school combines lectures, hands-on tutorials, and group projects to provide both the conceptual foundations and technical skills for the advanced modeling and analysis of behavior. The school is organized by the Centre de Recerca Matemàtica (CRM). Who should apply: The course is intended for PhD students and postdocs in cognitive, systems, and computational neuroscience with a solid background in computational or quantitative analysis. Proficiency in Python is required. We seek a diverse blend of experimentalists and theoreticians. A limited number of travel and childcare grants will be available. Scientists from underrepresented groups and countries are especially encouraged to apply. Topics covered: * Modeling fundamentals * Decision-making * Foraging and sequential decision-making * Reinforcement learning * Structure learning * Complex motor behaviors and time series Organizers: Alex Hyafil (CRM), Marion Rouault (CNRS, Paris Brain Institute), Heike Stein (CNRS, Sorbonne), Chris Summerfield (Oxford), Klaus Wimmer (CRM), Tarryn Balsdon (CNRS, ENS-PSL), Nisheet Patel (Axy), Manuel Molano-Mazón (UPC), Diksha Gupta (UCL), and Nuria Hernández (CRM). Keynotes: Megan Peters (UCI) and Marcelo Mattar (NYU). Guest Faculty: Mehdi Khamassi (ISIR, Sorbonne University) and Charley Wu (TU Darmstadt). We would be grateful if you could forward this announcement to interested students and colleagues. Best regards, The BAMB! 2026 Organizing Team info(a)bambschool.org @bamb-school.bsky.social ________________________________

Feb. 17, 2026

Reminder: Call for Application: Systems Vision Science Virtual Summer School & Symposium: July 8th – July 31st, 2026

by Pavlovic, Maria

Systems Vision Science Virtual Summer School & Symposium: July 8th - July 31st, 2026 -------------------------------- Applications are invited for a <https://summerschool.lizhaoping.org/virtual-systems-vision-science-summer-s chool-symposium-2024/> virtual edition of the Systems Vision Science Summer School and Symposium that took place in Max Planck Institute for Biological Cybernetics in Tuebingen, Germany in August 2023 <https://summerschool.lizhaoping.org/editions-in-previous-years/> and August 2025 and virtual in 2024. This year, the virtual edition enables students to attend from afar by formal lectures via Zoom and informal and social communications via a Slack channel. Systems Vision Science combines computational, behavioral, and neuroscience methods to discover functions and algorithms for vision in various brain regions and their implementations in neural circuits. This summer school is designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models. The syllabus content will be very similar to the edition in 2024 <https://summerschool.lizhaoping.org/points-policies-prizes/> . Experience or knowledge in (A) computational methods, (B) visual psychophysics, and (C) vision neuroscience, is not required. However, experience in at least one of (A), (B), and (C), and a readiness to learn, is expected. The Summer School will be followed by a Systems Vision Science Virtual Symposium on July 31st. All admitted summer school students will be invited to attend this symposium and are encouraged to submit for a presentation at the symposium. The symposium will also feature two invited keynote presentations. A certificate of completion of the summer school course will be provided after the student's successful completion of the summer school. -------------------------------- Important Dates: March 28, 2026 Deadline for applications April 10, 2026 Notification of acceptance April 27, 2026 Registration fees due July 8 - Virtual Systems Vision Science Summer School takes place July 30, 2026 (formal lectures via Zoom and informal and social communications via a Slack channel) July 31, 2026 Virtual Systems Vision Science Symposium takes place (3 -7 pm German time) -------------------------------- Please click here <https://summerschool.lizhaoping.org/application-virtual-svs/> to find more details and to apply by March 28, 2026. Summer School admission will be based on interest/motivation and prior knowledge/experience of the applicants, and on how much the applicants could benefit from participation. Please direct inquiries to svs.summerschool(a)tue.mpg.de <mailto:svs.summerschool@tue.mpg.de> -------------------------------- Organizing Team Li Zhaoping Maria Pavlovic Vladislav Aksiotis Franziska Lohrmann Max Planck Institute for Biological Cybernetics University of Tuebingen <http://www.lizhaoping.org> www.lizhaoping.org

Feb. 17, 2026

Join the Connectomics Revolution: Postdoctoral Researcher in Computational Neuroscience & EM Image Analysis

by Vikas

Dear Admin, Our lab, Kubota lab ( https://www.nips.ac.jp/eng/sp/research/researcher/assoc/post_79.html) in NIPS Japan is looking for the post doctoral candidates. It would be great if your can share the information with the members of comp-neuro. CC: Prof. Kubota. ------------------------------------------------------- Are you passionate about mapping the intricate wiring of the brain? The *Multi-Sensory Integration System Division (EM Team)* at the National Institute for Physiological Sciences (NIPS) in Okazaki, Japan, is looking for two talented researchers to join our mission in deciphering cortical circuits. We are integrating large-scale Volume Electron Microscopy (EM) to understand the structural basis of learning and memory. *We are looking for candidates who possess:* - A Ph.D. (or equivalent research track record). - *Strong Programming Skills:* Proficiency in Python, coding, and scripting. - *Technical Interest:* Experience or a keen interest in developing methods for image processing and analysis of large-scale EM datasets. - *Scientific Curiosity:* An interest in cortical connectomics and the computational understanding of neural circuits. *Why Join Us?* - Work at a world-class research institute in Japan. - Collaborate with Group Leader Yoshiyuki Kubota on cutting-edge connectomics projects. - Contribute to high-impact research. *Apply Today:* Find the full details and application instructions on J-REC-IN: https://jrecin.jst.go.jp/seek/SeekJorDetail?id=D126010223 Email : yoshiy(a)nips.ac.jp ( Yoshiyuki Kubota) Submit your CV, reprints of publications, summary of previous research and proposal, and 2 recommendation letters. ================================== The whole is greater than the sum of its parts. Aristotle =========================================== Vikas Pandey, Assistant Professor, WPI-PRIMe The University of Osaka Mail: pandey.vikas.prime(a)osaka-u.ac.jp <pandey.vikas.prime(a)osaka-hu.ac.jp> Tel: +81-6-6879-7716 ResearchGate <https://www.researchgate.net/profile/Vikas_Pandey> Linkedin <https://www.linkedin.com/in/vikas-pandey-73a97a1a4/> Google Scholar <https://scholar.google.com/citations?user=w4yD_gEAAAAJ&hl=en>

Feb. 17, 2026

Postdoc in computational neuroscience and machine learning

by Gershman, Samuel Joseph

The Computational Cognitive Neuroscience lab at Harvard University (PI: Sam Gershman) is recruiting a postdoc to work on projects at the intersection of computational neuroscience and machine learning, focusing on the role of memory in intelligent systems. This position is part of a collaborative grant with researchers at MIT and UC Berkeley. Start date: January 2027 or later Apply here: academicpositions.harvard.edu/postings/15868

Feb. 16, 2026

CNeuro2026 summer school in computational neuroscience, Beijing, July 2026

by Rava A. da Silveira

*CN**EURO**2026* *Theoretical and Computational Neuroscience Summer School* *7 to 14 July 2026 — Beijing, China* *This year: “C**ONNECTIONS BETWEEN **N**ATURAL* *AND **A**RTIFICIAL **I* *NTELLIGENCE**”* *www.cneuro.net* <http://www.cneuro.net> *Format* The course will bring together leading scientists in the field, who will deliver both introductory and advanced lectures, and take part in small-group discussions. Other activities will include homework sessions and student presentations, as well as the now popular “Life and Science” panel series, in which faculty and students can both share their personal experiences and views on research and career. *Faculty* Nathaniel Daw (Princeton University) Michael Häusser (The University of Hong Kong) Sukbin Lim (NYU Shanghai) Aravinthan Samuel (Harvard University) Haim Sompolinsky (Harvard University) Taro Toyoizumi (RIKEN Institute) Matthieu Wyart (EPFL and Johns Hopkins University) *Organizers* Rava Azeredo da Silveira (University of Basel and Unievrsity of Zurich) Sen Song (Tsinghua University) Louis Tao (Peking University) Xiaoqin Wang (Johns Hopkins University and Tsinghua University) Quan Wen (USTC) Hang Zhang (Peking University)

Feb. 16, 2026

NeuroBridges 2026 summer school – Registration Now Open

by David Hansel

*NeuroBridges 2026* *A Mediterranean, Middle Eastern Summer School in Neuroscience* *Deadline to apply: April 15th, 2026* *NeuroBridges 2026* is a summer school which will take place between *October 4 and* *October 15, 2026* in Le Centre de Conferences Internationales de Cluny, France (CCIC) <https://84454458.streak-link.com/Cxj80AMVlfndd-inKwgMJVkF/https%3A%2F%2Fcol…> . The school will provide an overview of theoretical and experimental frameworks used to study a variety of *decision making* processes. It will cover different model systems from rodents to humans and a plethora of decision making mechanisms. Another objective of Neurobridges is to bring together *Mediterranean and Middle Eastern scientists*, in order to promote scientific cooperation between young researchers from these countries. The organizers of NeuroBridges are convinced that such scientific collaborations can lead to personal relations, which eventually may alleviate the political distress in the Middle East. The school is intended for graduate students and postdocs, primarily, but not only, from the Middle East and the Mediterranean region, either working in their home countries or abroad. Applicants should have some background in related fields in neuroscience or cognitive psychology. *All costs of registration and accommodation will be covered by the organizers. A limited number of travel grants will also be available. In light of the ongoing situation in Iran, we are committed to providing full travel grants to all students coming from Iran.* *NeuroBridges 2026 Faculty:* Larry Abbott (Columbia University) Alaa Ahmed (University of Colorado) Eiman Azim (Salk Institute) Sharona Ben Haim (UC San Diego) Rava Azeredo da Silveira (IOB) Rasha Kardosh Israel Nelken (Hebrew University) Mathias Pessiglione (Paris Brain Institute) Drazen Prelec (MIT) Reza Shadmehr (Johns Hopkins University) *NeuroBridges* is co-organized by Ahmed El Hady (Max Planck Institute), David Hansel (CNRS), Yonatan Loewenstein (Hebrew University of Jerusalem) and Carole Levenes (CNRS). *NeuroBridges 2026* is supported by the Cyril Taylor Charitable Foundation, the Simons Foundation and ELSC, and is in partnership with VVTNS ( https://www.wwtns.online/) For more information and application, visit our website: https://neurobridges.net/ *Contact us:* neurobridges2026(a)gmail.com <neurobridges2023(a)gmail.com> ᐧ ᐧ

Feb. 16, 2026

World wide VVTNS series (6th season): Reading Minds & Machines | Wednesday, February 18, 2026, at 11:00 am ET - Michal Irani, The Weizmann Institute

by David Hansel

[image: VVTNS.png] https://www.wwtns.online <https://streaklinks.com/A9c7PbbpKY7PxB6PaAJWGD3-/https%3A%2F%2Fwww.wwtns.on…> - on twitter: wwtns@TheoreticalWide You are cordially invited to the lecture Michal Irani The Weizmann Institute on the topic of * Reading Minds & Machines* The lecture will be held on zoom on February 18, 2026, at *11:00 am ET * To receive the link: https://www.wwtns.online/register-page *Abstract: * 1. Can we reconstruct images that a person saw, directly from their fMRI brain recordings? 2. Can we reconstruct the training data that a deep-network trained on, directly from the parameters of the network? The answer to both of these intriguing questions is “Yes!” In this talk I will present some of our work in both domains. I will then show how combining the power of Brains & Machines can lead to significant breakthroughs in both areas, and potentially bridge the gap between Minds and Machines. Finally, I will show how combining the power of Multiple Brains (with NO shared data) may lead to new breakthrough discoveries in Brain-Science, and allow mapping of information between different brains. *About VVTNS : Launched as the World Wide Theoretical Neuroscience Seminar (WWTNS) in November 2020 and renamed in homage to Carl van Vreeswijk in Memoriam (April 20, 2022), Speakers have the occasion to talk about theoretical aspects of their work which cannot be discussed in a setting where the majority of the audience consists of experimentalists. The seminars, **held on Wednesdays at 11 am ET,** are 45-50 min long followed by a discussion. The talks are recorded with authorization of the speaker and are available to everybody on our YouTube channel.* ᐧ ᐧ

Feb. 15, 2026

DeepLearn 2026: early registration March 1st

by David Silva - IRDTA

****************************************************** 13th INTERNATIONAL SCHOOL ON DEEP LEARNING DeepLearn 2026 Orléans, France July 20-24, 2026 https://deeplearn.irdta.eu/2026/ ****************************************************** Co-organized by: University of Orléans Centre Val de Loire Doctoral College Institute for Research Development, Training and Advice – IRDTA Luxembourg/London ****************************************************** Early registration: March 1st, 2026 ****************************************************** SCOPE: DeepLearn 2026 will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Guimarães, Luleå, Bournemouth, Bari, and Porto. Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, biomedicine and healthcare, medical image analysis, recommender systems, advertising, fraud detection, robotics, games, business and finance, biotechnology, physics and astrophysics, biometrics, communications, climate sciences, geographic information systems, signal processing, genomics, materials design, video technology, social systems, earth and sustainability, mathematical proofs, etc. etc. The field is also raising a number of relevant questions about efficiency and robustness of the algorithms, explainability, transparency, interpretability, risks and safety, as well as important ethical concerns at the frontier of current knowledge that deserve careful multidisciplinary discussion. Most deep learning subareas will be displayed and main challenges identified through 16 four-hour and a half courses, 2 keynote lectures, 1 round table, and a hackathon competition among participants. Renowned academics and industry pioneers will lecture and share their views with the audience. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely. ADDRESSED TO: Graduates, postgraduates and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, hence people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2026 is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators. VENUE: DeepLearn 2026 will take place in Orléans, located in the heart of the Loire Valley, which was declared by UNESCO a World Heritage Site in 2000. The venue will be: University of Orléans Faculty of Law, Economics and Management 11 rue de Blois 45100 Orléans, France https://www.univ-orleans.fr/en STRUCTURE: 3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. All lectures will be videorecorded. Participants will be able to watch them again for 45 days after the event. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Also companies will be able to present their industrial developments for 10 minutes. The school will include a hackathon, where participants will be able to work in teams to tackle several machine learning challenges. Full live online participation will be possible. The organizers highlight, however, the importance of face to face interaction and networking in this kind of research training event. KEYNOTE SPEAKERS: Yingbin Liang (Ohio State University), Convergence Theory: How Fast Do Discrete Diffusion Models Generate? Le Song (Mohamed bin Zayed University of Artificial Intelligence), Multiscale Foundation Models for Biology PROFESSORS AND COURSES: Nitesh Chawla (University of Notre Dame), [intermediate] Learning from Imbalanced Data Yuejie Chi (Yale University), [introductory/intermediate] Statistical and Algorithmic Foundations of Reinforcement Learning Bo Han (Hong Kong Baptist University), [introductory/intermediate] Trustworthy Machine Learning from Data to Models Jiawei Han (University of Illinois Urbana-Champaign), [intermediate] Structure-Guided, Theme-Based Knowledge Discovery with Large Language Models Mingyi Hong (University of Minnesota), [intermediate] Modern Optimization Algorithms for Large Language Models Cho-Jui Hsieh (University of California Los Angeles), [intermediate/advanced] Optimizers for Large Language Model Training Furong Huang (University of Maryland), [advanced] Generative AI Agents Tara Javidi (University of California San Diego), [intermediate] Active Physical Intelligence for Industrial Scale Monitoring Yan Liu (University of Southern California), [intermediate] Time Series Foundation Models: From Forecasting to Reasoning Zhijin Qin (Tsinghua University), [intermediate/advanced] Semantic Communications Aarti Singh (Carnegie Mellon University), [intermediate] Human Centered AI: Challenges and Opportunities Suvrit Sra (Technical University of Munich), [introductory/intermediate] Introduction to the Theory of Learning with Transformers Ivor Tsang (A*STAR Centre for Frontier AI Research), [introductory/intermediate] Long-Horizon Agentic Intelligence Ming-Hsuan Yang (University of California Merced), [advanced] Recent Advances in Multimodal Understanding and Generation Tong Zhang (University of Illinois Urbana-Champaign), [introductory/intermediate] Reinforcement Learning for Large Language Models Jun Zhu (Tsinghua University), [introductory/advanced] Generative Models: from Virtual to Physical World OPEN SESSION: An open session will collect 5-minute voluntary oral presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david(a)irdta.eu by July 12, 2026. INDUSTRIAL SESSION: A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Abstracts have to be submitted to david(a)irdta.eu by July 12, 2026. HACKATHON: A hackathon will take place, where participants can voluntarily work in teams to tackle several machine learning challenges. They will be coordinated by Professor Sergei V. Gleyzer (University of Alabama). The challenges will be released 2 weeks before the beginning of the school. A jury will judge the submissions and the winners of each challenge will be announced by the end of August 2026. The winning teams will receive a modest monetary prize and the runners-up will get a certificate. SPONSORS: Companies/institutions/organizations willing to be sponsors of the event can download the sponsorship leaflet from https://deeplearn.irdta.eu/2026/sponsors/ ORGANIZING COMMITTEE: Karim Abed-Meraim (Orléans, local co-chair) Sergei V. Gleyzer (Tuscaloosa, hackathon chair) Meryem Jabloun (Orléans, local co-chair) Carlos Martín-Vide (Tarragona, program chair) Santiago Montes (Tarragona, webpage) Sara Morales (Luxembourg, finances) Florian Nowicki (Orléans, social networks) Philippe Ravier (Orléans, local chair) David Silva (London, organization chair) REGISTRATION: It has to be done at https://deeplearn.irdta.eu/2026/registration/ The selection of 6 courses requested in the registration template is only tentative and non-binding. For logistical reasons, it will be helpful to have an estimation of the respective demand for each course. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event. FEES: Fees comprise access to all program activities and lunches. There are several early registration deadlines. Fees depend on the registration deadline. The fees for on site and for online participation are the same. ACCOMMODATION: Accommodation suggestions are available at https://deeplearn.irdta.eu/2026/accommodation/ CERTIFICATE: A certificate of successful participation will be delivered indicating the number of hours of academic activities (40). This should be sufficient for those participants who plan to request ECTS recognition from their home university. QUESTIONS AND FURTHER INFORMATION: david(a)irdta.eu ACKNOWLEDGMENTS: Université d’Orléans Collège Doctoral Centre-Val de Loire Universitat Rovira i Virgili Institute for Research Development, Training and Advice – IRDTA, Luxembourg/London

Feb. 14, 2026

Visiting Assistant Professorship in Applied Mathematics at Northwestern University

by William L. Kath

* * /In addition to the details below, please note that the department has ties to the National Institute for Theory and Mathematics in Biology (NITMB) <https://www.nitmb.org/>//in downtown Chicago. / * Visiting Assistant Professorship in Applied Mathematics* The Department of Engineering Sciences and Applied Mathematics at Northwestern University (http://www.esam.northwestern.edu ) invites applications for the position of Visiting Assistant Professor in Applied Mathematics. This is a one-year, non-tenure-track position with the possibility of renewal for a second year. Duties involve teaching and research in applied mathematics with a focus on applications in engineering and/or the sciences. The Department seeks outstanding candidates who have received a Ph.D. degree in applied mathematics, engineering, physics or another applied math-related discipline, or who expect to do so by July 2026, and who aspire to engage in independent and interdisciplinary research and teaching. The starting date is September 1, 2026. The application package should include a cover letter, curriculum vita, statement of research accomplishments and interests, statement of teaching experience and philosophy, and if available representative manuscripts (published, submitted or in preparation). Please visit https://facultyrecruiting.northwestern.edu/apply/MjQ4Nw== to apply. In addition, the applicant should arrange for at least two, but no more than three letters of recommendation addressing both research and teaching qualifications. Recommendation letters will be automatically solicited from the letter writers by email after the names are entered in the online application system. *Compensation* The expected base pay range for this position is $78,000-$82,000 for a 12-month academic appointment and is subject to negotiation. Northwestern University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate, including years since terminal degree, training, and field or discipline; departmental budget availability; internal competitors; and external market pay for comparable jobs. At Northwestern, we are proud to provide meaningful, competitive, high-quality health care plans, retirement benefits, tuition discounts, and more! Visit us at https://www.northwestern.edu/hr/benefits/index.html to learn more. Questions may be directed to Noor Kaur at noor.kaur(a)northwestern.edu (subject line: Visiting Assistant Professor Search). To ensure full consideration, applications should be received by March 16th, 2026, but applications will be accepted until the position is filled. Northwestern University is an Equal Opportunity Employer and does not discriminate on the basis of protected characteristics, including disability and veteran status. View Northwestern’s non-discrimination statement. Job applicants who wish to request an accommodation in the application or hiring process should contact the Office of Civil Rights and Title IX Compliance. View additional information on the accommodations process. * Requirements* This is a one-year, non-tenure-track position with the possibility of renewal for a second year. Duties involve teaching and research in applied mathematics with a focus on applications in engineering and/or the sciences.

Feb. 12, 2026