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| 【有獎(jiǎng)交流】積極回復(fù)本帖子，參與交流，就有機(jī)會(huì)分得作者 努力打工的打工?的 5 個(gè)金幣 | |||||||||||
努力打工的打工?/a>新蟲 (初入文壇)
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[交流]
計(jì)算生物、化學(xué)、生物信息、結(jié)構(gòu)生物學(xué)方向
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一、aidd/cadd scientist→leader-上海 responsibilities: 1. support/drive early discovery projects from target identification/evaluation to hit identification, to lead optimization, and all the way to pcc and ind-enabling studies 2. contribute to the hit/lead optimization campaigns through mitigating any detected liabilities in terms of potency, selectivity, and adme/pk profiles 3. contribute to the global ai platform in optimizing current tools or establishing novel ai/machine learning models in cheminformatics and/or molecular modeling areas, which are applicable to discovery projects 4. proactively integrate experimental data and apply computational approaches to generate knowledge and insights requirements: 1. phd in computational chemistry/ biology, cadd, or any relevant areas that also bring the following set of skills and expertise 2. proficient in structure-/ligand-based drug design, including molecular docking, virtual screening, qsar, homology modeling, molecular dynamics, and quantum mechanics, etc., and master the relevant tools, including schrodinger, moe, discovery studio, etc. 3. proficient command of at least one programming language (python, c, c++, perl, shell, …) 4. highly motivated, possess excellent communication skills, enjoy working in multidisciplinary teams and are fluent in english 5. experience in ai/machine learning, data mining, and automate workflows is a plus 6. experience in the pharmaceutical industry or postdoctoral research in the drug discovery context would be a plus 7. good understanding of drug discovery principles including the fundamentals of medicinal chemistry, adme/pk and disease biology is a big plus 8. a track record of scientific contributions illustrated by publications and/or patents. extra points 1.expertise in machine learning (ml) and deep learning (dl), with experience in developingor applying ml/dl methods in at least one of the following fields: molecular propertyprediction, molecular generation, retrosynthesis prediction, protein design, biomedical textmining, or bioinformatics analysis, etc 2.experience in antibody and peptide generation or small molecule drug design for ppi would be a big plus. 二、抗體設(shè)計(jì)-北京 主要工作職責(zé)： 1.基于蛋白質(zhì)結(jié)構(gòu)分析和預(yù)測(cè)，抗原抗體對(duì)接等手段，設(shè)計(jì)點(diǎn)突變或者文庫(kù)，從多個(gè)維度優(yōu)化抗體藥物的特性，篩選有治療潛力的分子； 2.抗體人源化，親和力成熟，穩(wěn)定性優(yōu)化，雙特異抗體的設(shè)計(jì)等； 3.完成分子克隆的構(gòu)建，和團(tuán)隊(duì)一起驗(yàn)證蛋白質(zhì)優(yōu)化的設(shè)計(jì)； 4.及時(shí)分析匯報(bào)數(shù)據(jù)，幫助項(xiàng)目組做決定； 主要交付結(jié)果 1.作為治療性抗體發(fā)現(xiàn)團(tuán)隊(duì)的一員，完成抗體藥物的優(yōu)化設(shè)計(jì)并最終交付pcc分子； 2.獨(dú)立完成蛋白藥物的設(shè)計(jì)和相應(yīng)的克隆表達(dá)工作； 3.按時(shí)交付結(jié)果； 任職資格 教育和工作背景: 1.蛋白設(shè)計(jì)，結(jié)構(gòu)生物學(xué)相關(guān)領(lǐng)域博士以上學(xué)歷， 2年以上工作經(jīng)驗(yàn)； 2.深入了解蛋白結(jié)構(gòu)和功能，精通一個(gè)或多個(gè)常用的蛋白質(zhì)工程分子建模軟件包 （schrodinger, rosetta, moe, discovery studio）； 3.有蛋白質(zhì)工程化改造的研究經(jīng)驗(yàn)，如提高穩(wěn)定性，抗體人源化，親和力成熟，雙特異抗體設(shè)計(jì)等； 4.熟練掌握分子生物學(xué)技術(shù)，蛋白表達(dá)純化技術(shù)。 5.有雙抗/多抗設(shè)計(jì)經(jīng)驗(yàn)者優(yōu)先考慮 投遞請(qǐng)標(biāo)注：XX崗位+姓名+畢業(yè)院校+最高學(xué)位 KSX0928 charich.yp@x-giants.com [ 來(lái)自版塊群 上海 ] |
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