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Bioinformatics Litsebi Job lekhetho Template

Tsamaisa dinyakisiso sebelisa mekhoa bioinformatics le khopolo libakeng tsa lithethefatsi mohlala, theknoloji e ya kalafi dikhomphuitha baeloji, proteomics baeloji . Ka 'na Halli iphumanele mekhoa bakeng sa ho hlahloba le ho sebetsana lesedi genomic, kapa tse eketsehileng manyolo tlhahisoleseding le Listings.

Mosebetsi Tsebo ea mangolo
  • Boloka bapile ditlabelwa, biochemistries foreshe, kapa Software ka ho ba teng ho ea likopanong tse litsebi le hlahloba thepa ya kalafi.
  • Fana rekoto le liletsa dikhomphuitha bakeng sa ho hahamalla lintho biologically thehiloeng tse kang mohlala lefa and analysis, lintlha tsa liphatsa tsa lefutso-ho hlahisa maikutlo, le phatsa ea lefutso mosebetsi boikemisetso.
  • A tsamaise mosebetsi oa ho basebetsi thekenoloji lesedi phethahatsa le litsebi bioinformatics merero ea kapa lisebelisoa libakeng tse kang tsa bioinformatics mohlala hore ke ya kalafi, transcriptomics, metabolomics, le proteomics.
  • Hlahisa mananeo a hloekileng k'homphieutha kapa Customize Software hona joale ho khotsofatsa e itseng ea tleleniki ditlhoko mosebetsi.
  • Bopa ya data merero le Listings.
  • Hlahisa kapa fetola ho web thehiloeng bioinformatics mekhoa.
  • Style le sebelisa dikgatotharabololong bioinformatics ho akarelletsa le ba sa behoa leihlo le leihlo ho ithuta mochini, ntshetsopeleng sehlahlo, kapa dikgatotharabololong dikerafike.
  • Hlahisa litsela tsa foreshe dikhomphuitha le mekhoa e hlophisitsoeng as-hlokoa ke liphofu ho etsa lipatlisiso.
  • Ngola Info ho sebelisoa ka liketso mohlala bioinformatics hore ke mehaho le phatsa ea lefutso poleloana e reng profiling.
  • melemo e Converse ho etsa lipatlisiso ka libuka tsa bongaka, linehelano kopano e, kapa litlaleho tse mosebetsing.
  • Shape fumaneha hohle, khoebo proteomic Listings -genomic.
  • Hlahloba le bahlahlobisisi ba ho etsa lipatlisiso tse tsekoang, sisinya theknoloji e boithati likarabo, kapa theha mekhoa eo ke dikhomphuitha.
  • Hlahloba datasets kholo tse kang mohlala genomic letoto la lihlooho tse ya data tsa tlhaho ya data, le ya data ya data mabapi le mesebetsi ea tleleniki kapa mantlha ho etsa lipatlisiso.
  • Ho kgothaletsa tshebetso ho boost.
  • Batla keletso ho dikarolo tse kang mohlala kgothaletsa, ntshetsopeleng khoebo, le tshebetso ya ho bo nyalanya sehlahisoa ntshetsopeleng kapa tsoelo-pele.
  • Morero sebelisa ba mananeo Software ka liphetoho le tsoelo-pele ea bioinformatics Software ke hore khoebo.
  • Ho hlahloba ka mehlodi ya bioinformatics le kopo tse ntjha le.
  • Etsa kakaretso lipalo lintlha mabapi genomes batho.
  • Bolella ba bang ka har'a assortment le sebelisa ya lisebelisoa tse bioinformatics.
  • Eketsa likarolo motho ho bioinformatics Software le Listings.

Mosebetsi hahamalla lintho Hloka
  • Ho bala mela ea Kutloisiso-utloisise ka le serapa sa lokiseditsweng litokomane mosebetsi amanang.
  • Active-Ho mamela-fa temoho e oohle oa seo ba bang ba hona joale ba re, ho ipha nako ea hore u utloisise lintho tse neng li ntse li bōpileng, ho botsa lipotso e le loketse, 'me a sa stifling ka Maemong tse sa lokang.
  • Phatlalatsa-Ho bua ka katleho ka lengolo ha e le tse sa lokelang bakeng sa ditlhoko tsa bamameli.
  • Ho bua-ho bua ho batho ba bang ho abelana boitsebiso seng matsapa.
  • Thuto ea lipalo-U sebelisa lipalo ho lokisa mathata.
  • ditharollo ho etsa lipatlisiso-sebelisa le melao ea saense ho lokisa litseko tse tebileng le.
  • Mahlonoko tseo ho leng-Monahano-sebelisa lebaka le nahana ho lemoha makhabane a le go tlhoka mesola ea atamela, liqeto kapa ditharollo seng ho fapana mathata.
  • Active-Ithuta-Ho tseba liphello tsa lesedi foreshe ka bobeli a le teng le nakong e tlang ho rarolla mathata ho etsa liqeto le ho.
  • Ithuta ATAMELA-kha le ho sebelisa ho ruta / mekhoa thuto le mekhoa e nepahetseng bakeng sa bothata ha ho ithuta kapa webkataloge lintho tse ntjha.
  • Hlahloba-TrackingPEREvaluating bokgoni oa hao u le, batho ba tse fapaneng, kapa mekhatlo e nka bohato e lokisang kapa ho hlahisa lintlafatso.
  • Social Perceptiveness-Ka ho ba hlokomela likarabo othersA le kutloisiso ke hobane'ng ha ba arabela ha ba ntse ba etsa.
  • Tšebelisano tse fetolang liketso tsa ka litumeliso ba bang’ mehato.
  • Tšusumetso-atlehang ba bang ho fetola litloaelo kapa boko bona.
  • Negotiation-Ho Tlisa ba bang mmoho le batla ho lumellanya variances.
  • Ho thusa-ruta ba bang hore na joang ho etsa falla.
  • Company dikamano-ka mafolofolo o batla atamela ho thusa batho.
  • Advanced Bothata rarolleng-khetholla mathata rarahaneng le ho etsa lipatlisiso ya data e amanang le ho kenya tshebetsong dikgetho le ho ntshetsa pele le ho hlahloba bakhethoa.
  • Likhoebo tlhatlhobane mo go yone-Hlahlobisisa hloka le thepa e hlokang ho etsa moralo.
  • Engineering Design-Ho tloaela lisebelisoa kapa ho fehla motlakase le theknoloji ho sebetsa motho hloka.
  • Gear Selection-etsa qeto ea ka mofuta oa thepa le lisebelisoa tse hlokahalang ho etsa mosebetsi oa ka.
  • mananeo a instolmente-phaella, lihlahisoa, lithapo, kapa disebediswa ho khotsofatsa tobileng.
  • Coding-ne ba qapa dikopo khomphuteng bakeng dikopo fapaneng.
  • Tshebetso Tlhokomelo-Ho sheba matšoao eketsehileng, likotola, kapa litsupa ho etsa bonnete ba ha ho sa appliance jwale sebetsa ka nepo.
  • Tsamaiso le Control-thibela mesebetsi ya thepa kapa dithekeniki.
  • Thepa Maintenance-etsa ho bo boloka e le kemiso ka thepa le ho etsa qeto ha.
  • Tharollo ya mathata-beha lintlha morao glitches hore ba laola le ho khetha mokhoa oa ho tsoela pele ka eona.
  • Lokisa-lokisa dikai kapa dithekeniki sebelisa mekhoa tsa bohlokwa.
  • Boleng-Control Research-Ho etsa inspections le ditekolo tsa thepa, ditshebeletso, kapa ditsela tsa ho ahlola katleho kapa boleng.
  • Bohlale le Qeto etsang-Ho nahanela ditshenyehelo kakaretso le melemo tsa liketso tsa bokgoni ba ho fumana e mong hore e loketseng ka ho fetisisa.
  • Analysis-lekanngwang oa mofuta ofe lenaneo ba lokela ho sebetsa le hore na joang lintlafatso ka tikoloho, mesebetsi, hammoho le maemo a ka ama melemo e.
  • Mekhoa tlhatlhobane mo go yone-Khetholla mehato kapa litsupa ya tshebetso hammoho le mehato e ne e ena le tlhoko ea ho ntlafatsa kapa tshebetso nepahetse, amanang le ho lipakane tsa sesebediswa.
  • Nako-Management-Laola ka motsotso oa ba bang 'me nako e' ngoe ka boeena.
  • Tlhokomelo ea chelete-lekanngwang kamoo chelete e kenang e tla tloha e ile a qeta ho fumana mosebetsi finyelloa, le boikarabello bakeng sa ditshenyehelo tsena.
  • Management la Boitsebiso bo Mehlodi-Ho fumana le ho fumana ho tshebediso loketseng makgetheng, lisebelisoa, le thepa e hlokahalang bakeng sa ho etsa mosebetsi o itseng.
  • Tlhokomelo ea Basebetsi Resources-Building, ke ho khothatsang, le tsamaisa folks hobane ba sebetsa, beha batho ba molemo ka ho fetisisa bakeng sa mosebetsi oa hao.
koetliso ea ho hlokahala Experience Tlhokahalo
  • Lengolo la likharata
  • Thupelo Postdoctoral
  • Lengolo la thuto e phahameng ea masters
  • tse fetang 2 lilemo tse, ho fihlela-ho le ho akarelletsa le lilemo tse TSE LING
Mosebetsi Control Tsebo Tlhokahalo
  • AchievementORAttempt – 88.20%
  • ho phehella – 90.20%
  • Bohato ba Pele – 92.21%
  • Matla a ho Laela – 84.76%
  • thuso – %
  • Taba mabapi le ba Bang – 78.96%
  • Tataiso ea ho Etsa Metsoalle – 78.95%
  • Boitaolo – 85.71%
  • khatello ea monyako – 84.11%
  • VersatilityANDVersatility – 89.60%
  • tšeptjoang – 92.37%
  • A lebisa tlhokomelo ho Details – 91.72%
  • matla – 89.80%
  • tokoloho – 89.00%
  • ntshetsopeleng – 92.97%
  • katisediwa Monahano – 97.00%

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hlahloba Hape

Informatics ditsebi Tlhaloso Template

Sebelisa kutlwisiso ya hlokomela batho ba hōlileng ho thusa khōlong, ho moralo, me a tsoela pele phetolo ya e tsoetseng pele …

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