-1) { return true; } } return false; } /* Disable tracking if the opt-out cookie exists. */ if (__gtagTrackerIsOptedOut()) { for (var index = 0; index < disableStrs.length; index++) { window[disableStrs[index]] = true; } } /* Opt-out function */ function __gtagTrackerOptout() { for (var index = 0; index < disableStrs.length; index++) { document.cookie = disableStrs[index] + '=true; expires=Thu, 31 Dec 2099 23:59:59 UTC; path=/'; window[disableStrs[index]] = true; } } if ('undefined' === typeof gaOptout) { function gaOptout() { __gtagTrackerOptout(); } } window.dataLayer = window.dataLayer || []; window.MonsterInsightsDualTracker = { helpers: {}, trackers: {}, }; if (mi_track_user) { function __gtagDataLayer() { dataLayer.push(arguments); } function __gtagTracker(type, name, parameters) { if (!parameters) { parameters = {}; } if (parameters.send_to) { __gtagDataLayer.apply(null, arguments); return; } if (type === 'event') { parameters.send_to = monsterinsights_frontend.v4_id; var hookName = name; if (typeof parameters['event_category'] !== 'undefined') { hookName = parameters['event_category'] + ':' + name; } if (typeof MonsterInsightsDualTracker.trackers[hookName] !== 'undefined') { MonsterInsightsDualTracker.trackers[hookName](parameters); } else { __gtagDataLayer('event', name, parameters); } } else { __gtagDataLayer.apply(null, arguments); } } __gtagTracker('js', new Date()); __gtagTracker('set', { 'developer_id.dZGIzZG': true, }); if ( MonsterInsightsLocations.page_location ) { __gtagTracker('set', MonsterInsightsLocations); } __gtagTracker('config', 'G-NVR5VDVPSD', {"forceSSL":"true","link_attribution":"true"} ); window.gtag = __gtagTracker; (function () { /* https://developers.google.com/analytics/devguides/collection/analyticsjs/ */ /* ga and __gaTracker compatibility shim. */ var noopfn = function () { return null; }; var newtracker = function () { return new Tracker(); }; var Tracker = function () { return null; }; var p = Tracker.prototype; p.get = noopfn; p.set = noopfn; p.send = function () { var args = Array.prototype.slice.call(arguments); args.unshift('send'); __gaTracker.apply(null, args); }; var __gaTracker = function () { var len = arguments.length; if (len === 0) { return; } var f = arguments[len - 1]; if (typeof f !== 'object' || f === null || typeof f.hitCallback !== 'function') { if ('send' === arguments[0]) { var hitConverted, hitObject = false, action; if ('event' === arguments[1]) { if ('undefined' !== typeof arguments[3]) { hitObject = { 'eventAction': arguments[3], 'eventCategory': arguments[2], 'eventLabel': arguments[4], 'value': arguments[5] ? arguments[5] : 1, } } } if ('pageview' === arguments[1]) { if ('undefined' !== typeof arguments[2]) { hitObject = { 'eventAction': 'page_view', 'page_path': arguments[2], } } } if (typeof arguments[2] === 'object') { hitObject = arguments[2]; } if (typeof arguments[5] === 'object') { Object.assign(hitObject, arguments[5]); } if ('undefined' !== typeof arguments[1].hitType) { hitObject = arguments[1]; if ('pageview' === hitObject.hitType) { hitObject.eventAction = 'page_view'; } } if (hitObject) { action = 'timing' === arguments[1].hitType ? 'timing_complete' : hitObject.eventAction; hitConverted = mapArgs(hitObject); __gtagTracker('event', action, hitConverted); } } return; } function mapArgs(args) { var arg, hit = {}; var gaMap = { 'eventCategory': 'event_category', 'eventAction': 'event_action', 'eventLabel': 'event_label', 'eventValue': 'event_value', 'nonInteraction': 'non_interaction', 'timingCategory': 'event_category', 'timingVar': 'name', 'timingValue': 'value', 'timingLabel': 'event_label', 'page': 'page_path', 'location': 'page_location', 'title': 'page_title', 'referrer' : 'page_referrer', }; for (arg in args) { if (!(!args.hasOwnProperty(arg) || !gaMap.hasOwnProperty(arg))) { hit[gaMap[arg]] = args[arg]; } else { hit[arg] = args[arg]; } } return hit; } try { f.hitCallback(); } catch (ex) { } }; __gaTracker.create = newtracker; __gaTracker.getByName = newtracker; __gaTracker.getAll = function () { return []; }; __gaTracker.remove = noopfn; __gaTracker.loaded = true; window['__gaTracker'] = __gaTracker; })(); } else { console.log(""); (function () { function __gtagTracker() { return null; } window['__gtagTracker'] = __gtagTracker; window['gtag'] = __gtagTracker; })(); }

91看片网

Brown School › Academics › PhD in Social Work › Pre and Postdoctoral Training

Pre and Postdoctoral Training

T32 Training

The Brown School currently supports two NIH-funded T32 training programs for PhD students enrolled in our social work program and postdoctoral scholars already holding doctorates in social work and related disciplines, who are interested in addictions, mental health and/or implementation research. Both programs provide tuition fellowships, stipends, specialized coursework, and mentored research training for eligible applicants. 

NIMH Mental Health Services Research, Center for Mental Health Services Research

Transdisciplinary Training in Addictions Research (TranSTAR) T32 Program

  • Grant #: NIDA T32 DA 015035
  • Leopoldo Cabassa, Interim Co-Director; , Co-Director

Our trainees have been very successful in pursuing research funding through NIH and other competitive funding sources, and our alumni hold faculty positions at some of the nation鈥檚 top research institutions.

Predoctoral applicants:

Interested applicants must first apply and be accepted into the Brown School PhD Program in Social Work.

Evaluation is based upon previously received PhD program application materials, as well as the following, which must be additionally submitted:

  • One-page statement describing research interest in mental health services or addiction research.
  • In a resume-type format, please list:
    • Mental health or addictions-related professional education and licensure. Please include dates (month and year) of both degree programs and non-degree continuing education.
    • All employment after college and its relevance to mental health or addictions, in chronological order.
    • Prior research experience and its relevance to mental health or addictions.
    • All publications (full citation) and professional conference presentations.

Postdoctoral applicants:
Position vacancies vary throughout the year. Application materials must include the following:

  • Cover letter stating your research interests
  • CV
  • Three letters of reference

NOTE: Both pre- and post-doctoral applicants must be U.S. citizens or permanent residents of the United States at the time of award; citizenship eligibility is found .

Contact Stacey McCrary for additional eligibility requirements and position availability. The application review begins as soon as received and will continue until positions are filled.

Please email all materials to:

Stacey McCrary, MSW
Project Manager: NIMH/NIDA T32 programs 
stacey.mccrary@wustl.edu

NRT Training

AI-ACCESS National Research Traineeship

The NSF-funded AI Advancements and Convergence in Computational, Environmental, and Social Sciences (AI-ACCESS) National Research Traineeship (NRT) program at Washington University in St. Louis aims to build a cohort of new investigators, trained at the intersection of computational science (specifically AI), environmental science, and social sciences, with the skills to capitalize on the enormous synergistic potential in the convergence of AI and environmental social science. .