Manufacturing Futures Initiative (MFI) Postdoctoral Fellowship Program

Transcription

1 Manufacturing Futures Initiative (MFI) Pstdctral Fellwship Prgram I. Abut the MFI Pstdctral Fellwship Prgram The MFI Pstdctral Fellwship Prgram seeks candidates that will supprt the visin f MFI by demnstrating leadership in advanced manufacturing technlgies, artificial intelligence, integrated design and entrepreneurship, the science f learning, technlgy plicy, and the addressing challenges that crss multiple disciplines. Prpsed research must demnstrate a clear fit with the missin, research pillars and areas f academic inquiry and translatinal pprtunity f MFI. Bth internal and external applicants will be cnsidered. Applicants will need cnfirmed cmmitment frm a CMU faculty mentr t be cnsidered. Fellwship appintments will be fr ne year with the ptin fr renewal, subject t annual review and cnsideratin. II. Abut MFI Carnegie Melln University s Manufacturing Futures Initiative (MFI) is a campus-wide initiative that seeks t enable the future f manufacturing by bringing abut a new era f human-machine cllabratin that will advance manufacturing, the wrkfrce, and ecnmic develpment. MFI will highlight, strengthen, supprt, and advance five pillars f manufacturing research at CMU: 1

2 We are wrking t leverage machine learning, machine visin, and end-t-end data cllectin and analysis t accelerate the 20-year path frm discvery t cmmercial reality fr new materials and prcesses. We seek t clse the lp between materials and prcess discvery, design f prducts, wrkfrce training (frm scientists and technicians in the lab t designers f prducts t wrkers n the shp flr), and the regulatin f thse new technlgies by cnnecting the algrithms and data between scientists in the lab and the manufacturing shp flr. Why Carnegie Melln: Fields pineered at Carnegie Melln additive manufacturing, smart plymers, rbtics, and the Internet f things are amng the key technlgies transfrming prductin and the future f prducts. Tday, CMU faculty are discvering new advanced-material-based prducts frm self-assembled cellular systems t nn-txic energy generatin and strage, t micr-energetic macractuatrs. CMU is a glbal leader in cmputer science, basting nine Turing Award winning-faculty, plus three alumni, having defined the field f machine learning, and having the nly machine learning department in the wrld. CMU has als led the wrld in cmputatinal tls in design, innvatin and entrepreneurship: Integrated Prduct Develpment set the standard fr curses f its kind, and Quantitative Entrepreneurship is ne-f-a-kind in its methds. CMU s cmpany spin-ut rate is the highest f any U.S. academic institutin per federal research dllar invested, with half f CMU spinuts in manufacturing. CMU s Rbtics Institute, funded in 1979, is the leading rbtics research institute in the wrld. CMU s Simn Initiative has been transfrming educatin thrugh the science f learning. Finally, CMU is the leader in slving plicy prblems where the technical details matter. This wrld leadership in advanced manufacturing technlgies, artificial intelligence, integrated design and entrepreneurship, the science f learning, and technlgy plicy, cupled with CMU s unparalleled ability t wrk prblems at disciplinary bundaries, and the generus capital and infrastructure investment f a private dnr, are enabling CMU t envisin and accelerate the wrld int the physical and artificial future unlike any ther. 2

3 Interdisciplinary Cllabratin t Ignite the Manufactured Future Five areas f academic inquiry and translatinal pprtunity Accelerating materials and prcess discvery, Identifying new prduct pprtunities, Reinventing manufacturing systems and deplyment, Demcratizing wrkfrce training, and Aligning technlgy and innvatin plicy frm the interdisciplinary scaffld fr the Manufacturing Futures Initiative. Synergistically cutting acrss these five areas are applicatins f advanced data analytics t recgnize linkages and accelerate innvatin. In mre detail, these cmprise the fllwing activities: Accelerating Materials and Prcess Discvery: Leverage psychlgy, machine learning, machine visin and ther cmputatinal methds a) t ptimize the number and nature f physical experiments infrming material and prcess discvery, b) t autmatically identify micrstructural imperfectins and new frms, and c) t cnnect these imperfectins and new micrstructural frms t the surces f and science behind such frmatins, and infrm the creatin f new materials themselves. Identifying Prduct Opprtunities: Leverage design, cgnitive science, and machine learning t develp expert-guided algrithms t identify in which cmpnents t intrduce new advanced manufacturing technlgies and their ptimal designs. Reinventing Manufacturing Systems and Deplyment: Leverage rbtics, machine learning and machine visin fr in-situ prcess mnitring and cntrl that infrm micr-structural evaluatin 3

4 and prcess revisin in real time. Leverage rbtics, machine learning and machine visin t develp mdular, cllabrative rbtics fr flexible pst-prcessing and assembly. Demcratizing Wrkfrce Training: Develp AI-mediated and persnalized expertise transfer that can be accessed frm mbile devices anytime, anywhere. Aligning Technlgy Innvatin Plicy: Develp the mdels and data cllectin systems needed at the lcal and natinal level t enable crdinated technlgy develpment and wrkfrce develpment plicies, as well as the analysis f their impact. Clsing the Lp between Discvery and Cmmercializatin: Replace physical part inventry with knwledge inventry thrughut the life cycle f the part (prductin, micrstructure, and perfrmance in use), and leverage that knwledge fr just-in-time guidance fr discvery, repair, next-generatin part prductin, and regulatin f that next generatin. III. Eligibility Cmpletin f PhD r ScD prir t start date N mre than tw years past the date f the dctral degree at the time f appintment Internal and external candidates will be cnsidered IV. Applicatin Applicants are required t submit the fllwing materials. Applicatins will be judged n the qualificatins f the applicant, and the quality and applicability f the prpsed research t the missin and gals f the Manufacturing Futures Initiative and its ptential impact. Thesis abstract ne page Research prpsal 700-1,000 wrds (nt including references and citatins). Research prpsals must be aligned with the missin f MFI and demnstrate a clear fit with MFI research pillars and cre research areas crssing the pillars. Prpsals shuld be f high verall technical quality and represent nvel, interdisciplinary research. Submissins shuld als cnvey the impact f the prpsed research, including, as applicable, scial, ecnmic, plicy, and reginal impact as well as the ptential f the research t generate additinal funding. Educatin and backgrund statement wrds describing yur persnal backgrund and cntributins t advanced manufacturing thrugh yur academic career Curriculum vitae including publicatin list Writing sample sample publicatin r unpublished paper. Please limit t 35 pages (nt including references and citatins) 4

5 Tw letters f recmmendatin including ne frm the applicant s PhD thesis advisr, t be sent directly t CMU-MFI@andrew.cmu.edu, that prvide detailed assessments f the applicant s qualificatins and ptential fr innvative, grund-breaking independent research Letter f supprt frm the CMU faculty mentr wh will advise yu during yur fellwship appintment addressing: applicant s planned research extent t which the applicant will participate in department and campus activities and prgrams facilities and resurces available t the fellw statement cnfirming that the faculty mentr s department chair supprts the items abve NOTE: Applicants are encuraged t cntact faculty currently funded thrugh MFI as well as faculty with research interests that culd supprt MFI. V. Tenure The tenure f the pstdctral fellwship will be n less than 9 mnths and n mre than 12 mnths, with tenure beginning n earlier than June 1, 2018 and n later than September 1, Pstdctral fellwships may nt be deferred r delayed. Appintments may be renewed, subject t annual review and cnsideratin. VI. Stipend and Benefits One-year stipend: $60,000 Carnegie Melln University full-time staff benefits $10,000 will be prvided annually fr discretinary research expenses including travel VII. Submissin Prcedure Due date all applicatin materials must be submitted by 5:00 pm Eastern n January 29, 2018 Submissin prcess applicatin materials must be submitted via the CMU MFI Pstdctral Prgram nline applicatin frm Tw letters f recmmendatin including ne frm the applicant s PhD thesis advisr, t be sent directly t CMU-MFI@andrew.cmu.edu Candidates will be ntified n r befre February 15, 2018 Frmal acceptance f the fellwship must be made in writing n later than March 1,