- Comp-neuro - lists.cnsorg.org

Computational Psychology position at Tufts University

by Erin Munro Krull

Oct. 19, 2025

PhD Studentships in Computational Neuroscience at the University of Hertfordshire, UK

by Volker Steuber

PhD Studentship in Computational Neuroscience Biocomputation Research Group Centre for AI and Robotics Research School of Physics, Engineering and Computer Science University of Hertfordshire, UK Informal enquiries: Prof Volker Steuber, UH (v.steuber(a)herts.ac.uk) Dr Arnd Roth, UCL (arnd.roth(a)ucl.ac.uk) Application deadline: 14 November 2025 Studentship: approximately £20,700 per annum bursary plus payment of the student fees. Applicants from inside and outside the UK are eligible. Proposed Project: Reinforcement Learning and Microzones in the Cerebellum The crystalline structure of the cerebellar cortex has inspired the development of theories and computational models of learning in the cerebellum. In these computational models, learning is typically based on long-term depression (LTD) between parallel fibres and Purkinje cells in cerebellar cortex. More recently, however, plasticity has been shown to be present at different types of cerebellar synapses, and recent observations of reward signals conveyed by both mossy fibres and climbing fibres to the cerebellar cortex indicate that the roles of the instructive signals for cerebellar plasticity are more complex than assumed by classic theories. The presence of reward signals suggests that the cerebellum may be involved in reinforcement learning, by predicting the consequences of different actions. A further level of complexity arises from the existence of alternating cerebellar microzones that have been shown to contribute in different ways to cerebellar learning. The proposed PhD project will extend a previously developed detailed network model of the cerebellum. Simulations of the network model will be used to investigate the implications of reward signals and microzones for cerebellar learning. The work will contribute to a better understanding of learning in the cerebellum with potential applications in machine learning and neurorobotics. Applicants should have a keen interest in computational neuroscience and an excellent first degree or MSc in computer science, neuroscience, AI, machine learning, physics, maths, biology, medicine or a related discipline. The project involves a collaboration between the Biocomputation Research Group in the Centre for AI and Robotics Research at the University of Hertfordshire (Volker Steuber) and the Wolfson Institute for Biomedical Research at UCL (Arnd Roth) and will require regular visits to London. The Centre for AI and Robotics Research and the University of Hertfordshire provide a very stimulating environment, offering a large Doctoral School with many specialised and interdisciplinary seminars as well as general training and researcher development opportunities. The University is situated in Hatfield, in the green belt just north of London. Research in Computer Science at the University of Hertfordshire has been recognised as excellent in REF 2021, with 90% of the research submitted and all of the research impact rated as internationally excellent or world leading. Information on the application procedure and an application form can be found at: https://www.herts.ac.uk/study/schools-of-study/physics-engineering-and-comp… Volker Steuber Professor of Computational Neuroscience Biocomputation Research Group School of Physics, Engineering and Computer Science University of Hertfordshire College Lane, Hatfield, AL10 9AB, UK biocomputation.herts.ac.uk<http://biocomputation.herts.ac.uk>

Oct. 17, 2025

Postdoc position at U Oregon

by James Murray

A postdoc position is available with Prof. James Murray (murraylab.uoregon.edu) at the University of Oregon’s NeuroAI Center (ion.uoregon.edu/neuroai) Application link: https://academicjobsonline.org/ajo/jobs/30896 Position Summary -- In our research, our group seeks to uncover the principles of how the brain performs computations and implements learning related to motor control and sensory perception. Some of the scientific questions that motivate our work are - How do different regions of the brain interact to learn new motor skills? - What are the principles that enable brains and artificial agents to learn efficiently from experience while minimizing forgetting? - How can models of learning and motor control be synthesized across different levels of description? Our research group aims at building mechanistic models of brain function grounded in a combination of theoretical approaches, neural network-based simulations, and machine-learning analysis of experimental data. The candidate will have the opportunity to collaborate with a large network of experimental collaborators at University of Oregon and at other institutions with expertise in sensory processing (visual, auditory, and olfactory), motor control, naturalistic behavior, neural engineering, and brain-computer interfaces. While previous experience in computational neuroscience and machine learning are welcome, applicants from other quantitative fields (e.g. math, physics, statistics, computer science) who are eager to learn about neuroscience are encouraged to apply as well. The Oregon NeuroAI Center is part of the Institute of Neuroscience at the University of Oregon (ion.uoregon.edu) a major hub for systems and theoretical neuroscience research. The University of Oregon is located in Eugene, Oregon, a vibrant college town in the Pacific Northwest with ample cultural offerings and phenomenal access to outdoor recreation. We offer a competitive salary commensurate with the candidate’s experience, and remote work arrangements may be considered. Required Qualifications -- Successful candidates will have a PhD in a quantitative field, including physics, neuroscience, mathematics, statistics, computer science, or related fields. Applicants should have a strong quantitative background including at least some coding experience. Application -- Application link: https://academicjobsonline.org/ajo/jobs/30896 Application reviews will start on December 1st and will continue until the position is filled. Please send inquiries to jmurray9(a)uoregon.edu. Applications should include a CV, two-page statement of research interests, and contact information for three letters of reference.

Oct. 16, 2025

[Newsletter RTAIM] 22nd RTAIM Seminar | Call Abstract: Rio de Janeiro International Workshop: Ethics and Artificial Intelligence | Call for Papers (JAIC) | Others]

by steven gouveia

Dear All, You are welcome to attend the 22th rTAIM Online Seminar, with the participation of Markus Rüther (Jülich Research Centre and University of Bonn, Germany), 15 October 2025, 3:00pm - 4:30pm (Lisbon Time) via Microsoft Teams with the title “Meaningfulness Gaps in Medical AI". Link available: https://ifilosofia.up.pt/activities/seminar-22-rtaim Or: * Link: https://teams.microsoft.com/meet/3331048785485?p=LOIA0dGCgnqZXqSGdW * Meeting ID: 3331048785485 * Password: Yh2sE7zQ Moreover, the Call for Abstract for the Rio de Janeiro International Workshop: Ethics and Artificial Intelligence is still open until the 18 October 2025: https://trustaimedicine.weebly.com/rio-janeiro-workshop-ethics-ai.html New book out: “Ethics in Artificial Intelligence: A Multidisciplinary Approach”, Ethics Press. Info: https://ethicspress.com/products/ethics-in-artificial-intelligence Finally, paper submissions for a special issue on AI, 4E and Consciousness at the Journal of Artificial Intelligence and Consciousness is available here (deadline: 31 August 2025): https://www.worldscientific.com/page/jaic/callforpapers02. Sincerely yours, RTAIM Team

Oct. 15, 2025

Postdoc position in Digital twin brain for Alzheimer's Disease (Spase Petkoski, INS Marseille)

by Spase Petkoski

Job Offer: Postdoctoral Researcher in Digital Twin Brain for Prediction of Longitudinal Trajectories in Alzheimer’s Disease Location: Institut de Neurosciences des Systèmes <http://ins-amu.fr/>, Aix-Marseille University, France More info: https://ins-marseille.squarespace.com/jobs/job-posting-postdoc-alzheimer-1 Summary: We are recruiting a Postdoctoral Researcher for an ANR-funded project called Digital Twin Brain for prediction of longitudinal trajectories in Alzheimer’s Disease (AD). The postdoc will be based at Aix-Marseille University, at the Institut of Systems Neuroscience <https://ins-amu.fr/> in Marseille and will work under the lead of Spase Petkoski, INSERM CR (tenured researcher, equivalent to an Associate Professor), part of the Theoretical Neuroscience group led by Viktor Jirsa. A close collaboration is also envisaged with the clinical practitioners from the Neurology department of the public hospital at Marseille (APHM), the neurologists Mira Didic and Olivier Felician who work with patients with dementia, as well as with JF Mangin, the head of neuroimaging at Neurospin in Paris. As a postdoctoral researcher, the candidate will be responsible for developing and implementing computational models for the molecular mechanism of pathological proteins in AD into the whole-brain neuroinformatics platform The Virtual Brain <https://www.thevirtualbrain.org/tvb/zwei/> (TVB). Specifically, this will be done through glutamatergic and GABAergic synapses, utilizing existing neuronal mass candidates from the literature and from the previous work by the group. The model will also combine the mechanisms of prion-propagation. The modeling work will be accompanied by resting-state fMRI data analysis to identify the biomarkers of interest. The main cohort for the project will be Memento <http://www.memento-cohort.org/>, but ADNI3 <https://adni.loni.usc.edu/data-samples/adni-data/> will be also used. The candidate is thus expected to be familiar with concepts from Nonlinear Dynamics, in particular, solving and analyzing coupled ordinary differential equations. In the later stage, the project will also require an application of model inversion with simulation-based inference that should facilitate establishing links between the model parameter space and the neuroimaging data features. The latter will be a key component of this project and will also require addressing issues related to model degeneracy and resilience. The successful candidate will join a dedicated team developing models and methodologies for better explanation of neuroimaging data. This work has a broader impact than AD, it will establish an interpretable link across scales from synapses to neuronal populations (the network nodes in TVB), and significantly amplify the effectiveness of TVB in comprehending multiscale effects within brain networks. This, in turn, will facilitate the enhanced usability of digital twins in the clinical context and in diagnosing brain health status. Required Qualifications: PhD (or equivalent) in computational neuroscience or related discipline. Experience in one or more of the project research topics, including Brain Network Models, Dynamical systems, Prion Spreading, Machine Learning, and Alzheimer’s Disease. Proficiency in programming with Python, with expertise in scientific computing packages. Proficiency in spoken and written English. Desired Qualifications: Background in neuroscience. Familiarity with TVB. Experience running parallelized large-scale simulations on supercomputers. Expertise in time-series analysis, data science and data visualization. About The Theoretical Neuroscience Group: We are a multinational and interdisciplinary team dedicated to unraveling the spatiotemporal organization of large-scale brain networks. Our work encompasses mathematical and computational modeling of large-scale network dynamics, the analysis of human brain imaging data, and the development of neuroinformatics tools for studying large-scale brain networks, particularly in the context of brain disorders such as epilepsy, Alzheimer's disease, and multiple sclerosis, and healthy aging. The group is heavily involved in developing standard models for digital twins in the infrastructure project of EBRAINS <https://www.ebrains.eu/>. Terms of Employment: This is a fully funded multi-year position with excellent benefits. The initial appointment is for one year, with the potential for extension up to 3 years. Salary will be commensurate with experience. Application Deadline: November 10th. Starting Date: January 2026 How to Apply: Please send a CV, a short cover letter describing your research interests, and contact details for 2–3 referees to spase.petkoski(a)univ-amu.fr <mailto:spase.petkoski@univ-amu.fr>. We look forward to welcoming a highly motivated and qualified postdoctoral researcher to our team to advance our understanding of large-scale brain network models in the context of Alzheimer’s Disease and to move closer to real digital twins of the brain.

Oct. 15, 2025

PhD position in cognitive computational neuroscience

by Mingbo Cai

*PhD position in cognitive computational neuroscience * The lab led by Dr. Mingbo Cai at University of Miami ( https://cailab-miami.org/) has a PhD position open for Fall 2026. Students with computational background and/or experience with neuroimaging are highly encouraged to apply. The lab has an ongoing project on fMRI study of decoding spontaneous thoughts and we are looking for a student excited about this area, either for basic science or mechanistic study of rumination and worry. Students interested in using computational modeling and novel cognitive tasks to study decision making and learning, as well as computational psychiatry, are also welcome to apply. The deadline of application is December 1, 2025. Please apply through the cognitive and behavioral neuroscience division: https://www.psy.miami.edu/graduate/doctoral-programs/index.html Mingbo Cai Assistant Professor Department of Psychology University of Miami

Oct. 15, 2025

Scholarships available for BCCN Berlin International Doctoral Program Computational Neuroscience

by GraduatePrograms

Dear colleagues, we at the Bernstein Center for Computational Neuroscience Berlin are happy to announce that we have two DAAD-funded scholarships for doctoral students available! We will select two excellent doctoral student candidates to receive scholarships from the DAAD as part of the Graduate School Scholarship Program (GSSP). * The scholarships begin in October 2026 à 1,300€/ month, for up to a maximum of 4 years, * In addition to the scholarship, health insurance, accident insurance, and liability insurance will be covered by the DAAD, * Scholarship recipients can also receive assistance for their rent payments, * Scholarship recipients with families may receive additional funding, * Scholarship recipients will have access to a country-specific travel budget from the DAAD, * Scholarship recipients will have access to additional Study and Research grants, * Can have German courses financed by the DAAD. To be eligible for the GSSP scholarships, the student must: * Have an excellent academic profile and must have completed their master's (or equivalent) by the start of the funding period (October 2026), * Can not have completed their master's (or equivalent) more than 6 years ago, * At the time of application (March 2026), can not have been a resident in Germany for more than 15 months, * Can not already have a PhD, * Can not perform more than 25% of their doctoral work outside of Germany, and external work can not take place at the start of the doctoral project. To be awarded the GSSP scholarship, the student must: 1. Apply to the BCCN PhD program -->*Application deadline March 15th 2026!* 2. A member of the BCCN Berlin must agree to supervise and accept the student to their group for the duration of their PhD. 3. A project proposal outlining the general goals of the doctoral project must have been agreed upon by the student and the BCCN Berlin supervisor by the application deadline. For more information on how to apply to the International Doctoral Program Computational Neuroscience of the BCCN Berlin, please see our website: https://www.bccn-berlin.de/doctoral-program-application.html Finally, we organize an Information session about our graduate programs which will take place in January 2026: https://www.bccn-berlin.de/events-list/information-day-2026-international-g… Please share this information with anyone who may be interested. Best regards, Lisa Velenosi -- Dr. Lisa Velenosi Teaching Coordinator of the SFB1315 & BCCN Berlin Humboldt-Universität zu Berlin Philippstraße 13, Haus 6; 10115 Berlin; Germany Tel: +49 (0)30 2093-98503

Oct. 14, 2025

CALL FOR SYMPOSIA PROPOSALS: AISB 2026, University of Sussex

by Simon Bowes

CALL FOR SYMPOSIA PROPOSALS: AISB 2026, University of Sussex (DEADLINE: November 30, 2025) Contact: Simon Bowes (S.C.Bowes(a)sussex.ac.uk<mailto:S.C.Bowes@sussex.ac.uk>) AISB 2026 will be held at the University of Sussex on the 1st-2nd July. For more information on the convention please see the website at https://aisb.org.uk/. Keynote Speaker: Anil Seth The AISB 2026 convention will follow the same overall structure as previous conventions, namely a set of co-located symposia, and we are seeking proposals for these symposia. Typical symposia last for one or two days, and can include any type of event of academic benefit: talks, posters, panels, discussions, demonstrations, outreach sessions, etc. Proposals for Symposia are welcomed in all areas of AI and cognitive science. Some suggested areas are shown below, although any proposal in the field of AI or cognitive science will be welcomed: · AI in Education · Agency & AI · Art & AI · Cognitive & Computational Neuroscience · Computational theory of mind · Computational Intelligence · Consciousness · Embodiment and AI · Ethics of AI · Human and Machine Creativity · Hybrid Human-AI · Knowledge Representation · Machine Learning · Robotics · Bio-inspired approaches. · Simulation of Human and Animal Behaviour · The Turing Test and Philosophical Foundations of AI -------------------------------------------------------------------------------- Proposing a Symposium Each symposium is organized by its own programme committee. The committee proposes the symposium, defines the area(s) and structure for it, issues calls for abstracts/papers etc., manages the process of selecting submitted papers for inclusion, and compiles an electronic file for inclusion in the convention proceedings. Proposers are welcome to submit or be involved with more than one proposal. Proposers need not already be members the AISB and will not be required to become members. They will of course be encouraged to join! Deadline for symposium proposals: 30th November 2025 Notification of acceptance: 15th December 2025 -------------------------------------------------------------------------------- Submissions should consist of the following - A title. - A 300–1000-word description of the scope of the symposium, and its relevance to the convention along with the nature of the academic events (talks, posters, panels, demonstrations, etc.). - Whether the symposium is intended as a sequel to a symposium at a previous AISB conference. - An indication of whether submissions will be by abstract, extended abstract, or full paper. - Your preferences about the intended length of the symposium as a number of days (half a day, one day or two days), together with a brief justification. - A description (up to 500 words) of any experience you have in organization of academic research meetings (please note that it is not a requirement that you have such experience). - Names and affiliations of any invited speakers that you may have in mind for the symposium. - Your names and full contact details, together with, if possible, names and workplaces of the members of a preliminary, partial programme committee. - Please e-mail your completed proposal to Simon Bowes: S.C.Bowes(a)sussex.ac.uk<mailto:S.C.Bowes@sussex.ac.uk>

Oct. 14, 2025

AAAI 2026 workshop "Neuro for AI & AI for Neuro: Towards Multi-Modal Natural Intelligence"

by Anton Arkhipov

Dear Colleagues, An update and a friendly reminder about the Workshop “Neuro for AI & AI for Neuro: Towards Multi-Modal Natural Intelligence” at the AAAI 2026 conference in Singapore on January 27, 2026. Thanks to those who submitted their papers so far, and we are looking forward to all your submissions by October 30, 2025. Updated list of confirmed speakers: * Guozhang Chen (Peking University) * Dmitri "Mitya" Chklovskii (Flatiron Institute, NYU) * Elisa Donati (University of Zurich and ETHZ) * Adrienne Fairhall (Universtiy of Washington) * Patrick Mineault (Amaranth Foundation) * Adeel Razi (Monash University) * Martin Schrimpf (EPFL) * Mike Zheng Shou (National University of Singapore) * Andreas Tolias (Stanford University) Please see details below and at https://neuroai-multimodal-workshop.github.io/. We invite submissions of full papers or abstracts that describe new research, work in progress, or position statements on relevant topics. Original, unpublished submissions may be considered for a special issue on "Neuroscience and AI" in the Journal of Neural Engineering. The full paper submissions should be 8 pages maximum, excluding references, and the abstract submissions should be 2 pages maximum, excluding references, in the AAAI two-column format. Please submit your work by October 30, 2025 at https://openreview.net/group?id=AAAI.org/2026/Workshop/NeuroAI. Organizing Committee: * Reza Abbasi-Asl, University of California, San Francisco * Asim Iqbal, Tibbling Technologies / Weill Cornell Medicine * Sophia Sanborn, Stanford University * Shinya Ito, Allen Institute * Anton Arkhipov, Allen Institute * Naomi Donovan, University of California, San Francisco * Macarena Aloi, Allen Institute Description of workshop: This workshop will unite researchers in artificial intelligence, computational neuroscience, and neuromorphic engineering to explore the critical two-way exchange between biology and machine learning. Our main objective is to bridge these fields to accelerate foundational progress in multimodal natural intelligence. The “Neuro → AI” theme will investigate how principles from cortical microcircuits, such as sparse coding, dendritic nonlinearities, and cell-type diversity, can inspire novel, efficient, and robust AI architectures like transformers and graph-based models. Conversely, the “AI → Neuro” theme will showcase how advanced machine-learning techniques are revolutionizing neuroscience, enabling new insights into neural dynamics through AI-driven analysis of large-scale imaging, electrophysiological, and behavioral data. By bridging the gap between biologically grounded inductive biases for AI and scalable computational tools for neuroscience, this workshop aims to catalyze research that unifies theory, experiment, and application. Topics: * Biologically inspired machine learning architectures * Neuro-inspired mechanisms for efficiency (e.g., sparsity, inhibitory-excitatory balance) * AI-driven analysis of large-scale neuroscience data * Unsupervised representation learning and causal inference for circuit discovery * Gradient descent-based training of bio-realistic neural models * Open-source software and reproducible research in NeuroAI * Neuromorphic engineering and hardware implementation Format of Workshop: This will be a one-day, in-person workshop. The format is designed to be highly interactive, featuring a series of invited talks from world-renowned experts, two panel discussions for in-depth Q&A, and spotlight presentations for high-impact contributed papers. A central poster session will provide a forum for detailed discussion and networking. The day will conclude with a roundtable discussion to identify key community challenges and a sponsored social gathering to foster continued collaboration. Attendance: We welcome researchers and practitioners from academia and industry with an interest in the intersection of neuroscience and artificial intelligence. At least one author of each accepted submission must be present at the workshop. The maximum number of attendees is to be determined by the room size and will be communicated by AAAI. Please reach out if you have any questions. We look forward to seeing you in Singapore! Best regards, Reza Abbasi-Asl, Asim Iqbal, Sophia Sanborn, Shinya Ito, Anton Arkhipov, Naomi Donovan, Macarena Aloi Anton Arkhipov Investigator, Allen Institute antona(a)alleninstitute.org<mailto:antona@alleninstitute.org> alleninstitute.org<https://alleninstitute.org> brain-map.org<https://portal.brain-map.org/>

Oct. 14, 2025

Open Rank Faculty Position in Artificial Intelligence in Psychological Science

by Stacie Warren

*Open Rank Faculty Position in **Artificial Intelligence in Psychological Science* *Position Description* The Department of Psychology in the School of Behavioral and Brain Sciences (BBS) at The University of Texas at Dallas (UT Dallas) is accepting applications for a tenure system position for a faculty member whose work interfaces with artificial intelligence (AI). Candidates with postdoctoral training or equivalent research experience are preferred, especially those who have led or contributed to multidisciplinary teams bridging psychology with computer/data science. We welcome profiles spanning: (a) ML/AI as advanced statistics; (b) core AI/generative technologies; and (c) computational social science. Strongest consideration may be given to applicants who apply modern AI pipelines and tooling to substantive psychological questions. Evidence of an emerging or established record of high-impact publications; experience building reproducible, well-documented code and analyses; and potential (or success) for extramural funding are highly valued. Ideal candidates can connect AI methods to psychological theory (e.g., cognitive modeling, language and social behavior, clinical assessment, developmental science), teach AI-in-Psychology courses effectively, and mentor students from a range of backgrounds. Preference will be given to applicants who demonstrate responsible/ethical AI practices, open science commitments, and a collaborative approach that enhances BBS research centers and cross-school partnerships. Candidates at all levels will be considered. Teaching responsibilities could include undergraduate and graduate level courses in artificial intelligence in psychology, cognitive science, and/or courses in the applicant’s area of expertise, as well as mentoring of doctoral, master’s-level, and undergraduate students. The appointment commences for the fall 2026 semester. *Qualifications* Minimum Education and Experience: A PhD or equivalent in Psychology, Cognitive Science, or a related discipline is required prior to appointment. Candidates are expected to demonstrate the ability to work effectively in a highly collaborative, engaging, and dynamic environment comprised of individuals with a range of backgrounds, skills, and perspectives. We are seeking candidates able to produce research and scholarly or creative achievements that enhance the program and the discipline, and able to deliver high quality teaching using evidence-based practices to effectively engage students from a range of backgrounds and experiences. Candidates are expected to demonstrate clear potential for (at the Assistant Professor rank), or an existing track record of, obtaining and maintaining extramural research funding. *UT Dallas School of Behavioral and Brain Sciences and the Department of Psychology* The University of Texas at Dallas is a Carnegie R1 Research Institution and is among the fastest growing universities in the nation. The School of Behavioral and Brain Sciences (BBS) is one of seven schools at UT Dallas and ranked 2nd in total new research grants and research expenditures over the past year. Within its walls, the School of Behavioral and Brain Sciences (BBS) stands uniquely positioned to advance knowledge and improve lives through the efforts of its 111 faculty and 3,000 students. In North Texas, BBS serves as a trailblazer where research, education, and clinical training come together to prepare future leaders. It is home to world-class faculty with work ranging from bench-top to bedside studies, and ample resources and opportunities for students and faculty alike. In the past year, BBS was recognized by the BlueRidge Institute for being #1 in Texas and #3 in the United States for NIH funding for schools of its type. Within BBS, faculty members are surrounded by colleagues who interface with science and technology at every level of translation – with a keen focus on using our science to impact the health and well-being of people around the world while training the scientific leaders of tomorrow. Collectively, BBS leads UT Dallas in R&D rate and new awards per faculty member as well as many student success metrics across the university. The Department of Psychology is one of three departments within the School of Behavioral and Brain Sciences. The department houses 44 faculty and has almost 1,400 students. The Department of Psychology was responsible for over $12 million in new extramural grants in the past year and is home to a large number of multi-grant funded faculty members. The department has a distinguished legacy of world class research across cognitive neuroscience and developmental science. It also houses multiple pioneering AI-engaged faculty innovating in the fields of cognitive science and human-computer interface research. The Department has a rich history of housing well-known research centers that lead their respective fields around the globe. For example, psychology faculty are active participants in several BBS affiliated research centers at UT Dallas including the Center for BrainHealth, Center for Vital Longevity, and Center for Children and Families, with multiple centers led by Psychology faculty. The Department of Psychology is home to the BS in Psychology, BS in Cognitive Science, and BS in Child Learning and Development. It is also home to the MS in Psychology, the MS in Human Development and Childhood Disorders, and the PhD in Psychology. It also shares degree programs with the Department of Neuroscience for the MS in Applied Cognition and Neuroscience and the PhD in Cognition and Neuroscience. The BS in Psychology represents the 7th most popular undergraduate major at UT Dallas. In fall 2026, we will enroll our first cohort of Clinical Psychological Science PhD students along with the opening of our Psychological Sciences and Education Center in summer 2026. *Application Instructions* Applicants should upload the following via the online application <https://jobs.utdallas.edu/postings/30422>: · Full curriculum vitae and cover letter summarizing their interests and qualifications for the position. · Statement of teaching philosophy describing their conceptualizations of teaching and learning, and teaching and assessment methods, and how their teaching practices will engage students from a range of backgrounds and experiences. · Research statement describing past, present, and future research, including how they mentor (or will mentor) student researchers and foster (or will foster) collaborative research environments. · Full contact information for at least three academic or professional references. Priority will be given to completed applications received by *December 1, 2025*. Reviews will continue until the position is filled or the search is closed on March 1, 2026. *The University and Community * UT Dallas is a top public research university located in one of the nation’s fastest-growing metropolitan regions. Our seven schools offer more than 140 undergraduate and graduate programs, plus professional certificates and fast-track programs. Our student body is approximately 30,000 strong, reflecting students from over 100 countries and a multiplicity of perspectives and experiences. Over 65% of our undergraduate students receive some form of need- or merit-based financial aid; and 66% of graduating seniors have no student debt compared to 48% in Texas and 32% in the nation (2021 TICAS report). UT Dallas is committed to graduating well-rounded members of the community whose education has prepared them for rewarding lives and productive careers in a constantly changing world. Our mission centers on providing Texas and the nation with excellent and innovative education and research. The University’s rapid growth is fueled by our creative and enterprising spirt, bright students, innovative programs, renowned faculty, dedicated staff, engaged alumni, and research that matters. The University promotes a welcoming environment through programs and initiatives designed to support engagement and success for members of the campus community. Employee benefits include a range of physical and mental wellness resources, competitive insurance and retirement plan options, lactation facilities located throughout the campus, and Employee Resource Groups (ERGs) comprised of individuals who share common interests to help build community among UT Dallas faculty and staff (e.g., Universal Access ERG, Military and Veteran ERG, UT Dallas Young Professionals). Additionally, the University’s modern campus, 400+ campus organizations, and prime location foster collaboration and community. Situated in Richardson, Texas, the University’s location offers abundant professional development and entertainment options. The Dallas-Fort Worth (DFW) metroplex is rich with visual and performing arts venues, museum districts, professional and semi-professional athletics teams, botanical gardens, accessible trails, and much more, ensuring there’s something for everyone. The University’s partnerships with regional higher education institutions, local school districts, numerous companies, and the Richardson Innovation Quarter <https://richardsoniq.com/> (Richardson IQ) – a major hub for innovation, entrepreneurship, and educational activities – promotes collaboration, professional growth, and educational excellence. *Equal Employment Opportunity * The University of Texas at Dallas is committed to providing an educational, living and working environment that is welcoming, respectful, and inclusive of all members of the university community. The University prohibits unlawful discrimination <https://policy.utdallas.edu/utdbp3090> against a person because of their race, color, religion, sex (including pregnancy), sexual orientation, gender identity, gender expression, national origin, age, disability, genetic information, or veteran status. -- Stacie L. Warren, Ph.D. Associate Professor Department of Psychology School of Behavioral and Brain Sciences The University of Texas at Dallas 800 West Campbell Road, GR 41 Richardson, TX 75080 Phone: (972) 883-3818 E-mail: stacie.warren(a)utdallas.edu <sholub(a)utdallas.edu>

Oct. 13, 2025