求人・転職情報
4件中の1〜4件を表示
仕事内容
神経変性疾患および神経筋疾患を含むさまざまな神経疾患を対象とした新規治療薬について、定量的数理モデルを構築し、創薬の研究開発における意思決定を推進します。
前臨床生物学／薬理、ケミストリー／バイオロジクス、前臨床安全性評価、トランスレーショナルメディシン、臨床薬理および臨床開発などのクロスファンクショナルチームと協働し、標的とする生物学的経路と新規治療薬の相互作用、およびそれらが病態進行に与える影響について、数理モデルに基づいて理解を深めることに貢献します。
チームを巻き込んだ最適なモデリング＆シミュレーション戦略を立案し、実行します。創薬候補物質の選択、試験デザインの最適化、バイオマーカー選択に関する意思決定を支援・加速するため、トランスレーショナルなPK/PD/efficacy model, mechanistic modelあるいはsystems modelを設計・構築します。
臨床試験に向けて、ヒトでの薬理活性／有効用量、投与スケジュール、安全域を予測します。そのために、臨床段階の比較薬から得られるベンチマーキング情報や、それらのリバーストランスレーションから得られる知見を有効に活用します。
Drive decision-making in drug discovery and development by building a quantitative model of novel therapeutic agents to treat various neurological diseases including neurodegeneration and neuromuscular diseases.
Work on cross-functional teams with preclinical biology/pharmacology, chemistry/biologics, nonclinical safety assessment, translational medicine, clinical pharmacology and clinical research to develop a quantitative model-based understanding of the interactions of target biological pathways and novel therapeutic agents, and their impact on disease progression.
Formulate and implement team-engaged right modeling & simulation strategy. Design and build translational PK/PD/efficacy and mechanistic and/or systems models to assist and accelerate decisions around drug candidate selection, study design optimization as well as biomarker selection.
Enable translational predictions of human pharmacologically active/efficacious dose, dosing schedule and safety margin for clinical trials. Leverage clinical benchmarking insights from clinical comparators and/or their reverse translation.
前臨床生物学／薬理、ケミストリー／バイオロジクス、前臨床安全性評価、トランスレーショナルメディシン、臨床薬理および臨床開発などのクロスファンクショナルチームと協働し、標的とする生物学的経路と新規治療薬の相互作用、およびそれらが病態進行に与える影響について、数理モデルに基づいて理解を深めることに貢献します。
チームを巻き込んだ最適なモデリング＆シミュレーション戦略を立案し、実行します。創薬候補物質の選択、試験デザインの最適化、バイオマーカー選択に関する意思決定を支援・加速するため、トランスレーショナルなPK/PD/efficacy model, mechanistic modelあるいはsystems modelを設計・構築します。
臨床試験に向けて、ヒトでの薬理活性／有効用量、投与スケジュール、安全域を予測します。そのために、臨床段階の比較薬から得られるベンチマーキング情報や、それらのリバーストランスレーションから得られる知見を有効に活用します。
Drive decision-making in drug discovery and development by building a quantitative model of novel therapeutic agents to treat various neurological diseases including neurodegeneration and neuromuscular diseases.
Work on cross-functional teams with preclinical biology/pharmacology, chemistry/biologics, nonclinical safety assessment, translational medicine, clinical pharmacology and clinical research to develop a quantitative model-based understanding of the interactions of target biological pathways and novel therapeutic agents, and their impact on disease progression.
Formulate and implement team-engaged right modeling & simulation strategy. Design and build translational PK/PD/efficacy and mechanistic and/or systems models to assist and accelerate decisions around drug candidate selection, study design optimization as well as biomarker selection.
Enable translational predictions of human pharmacologically active/efficacious dose, dosing schedule and safety margin for clinical trials. Leverage clinical benchmarking insights from clinical comparators and/or their reverse translation.
求める経験 / スキル
化学工学／生物医学工学、製剤・薬学、数学、物理学分野などのMS／PhD／PharmDを有すること
数理モデル構築の高い能力（MATLAB、SimBiology、NONMEM、Monolix、Phoenix、Python、Rなど一般的に用いられる言語／ツールのいずれかの使用経験）
生体システムの数理モデルを用いた定量的解析を行った経験。特に、神経疾患領域にモデリング＆シミュレーションアプローチを適用した経験、もしくはその分野への強い関心があることが望ましい
複雑な情報を解析し、重要な科学的問いを特定できる優れた分析能力
複雑な数理モデル解析の結果を、クロスファンクショナルなチームメンバーに対して、分かりやすく簡潔に伝えるコミュニケーション能力
グローバルチームの下で業務を推進していくための、読み書き及び会話の両面での良好なビジネス英語力（TOEICスコア750点以上など）
MS/PhD/PharmD in chemical or biomedical engineering, pharmaceutical sciences, mathematics, physics, or equivalent area.
Strong competency in building mathematical models is required (in commonly used languages such as MATLAB, SimBiology, NONMEM, Monolix, Phoenix, Python, or R)
Experience in mathematical modeling of biological systems. Especially, an experience and/or interest in applying modeling and simulation approaches to neurological diseases is preferred.
Demonstrated strong analytical skills to evaluate complex information and identify key scientific questions.
Ability to communicate complex modeling results clearly and concisely to cross-functional audience is critical.
Good English communication skill in both written and verbal (TOEIC score ≥750, etc.) to work under global team setting
数理モデル構築の高い能力（MATLAB、SimBiology、NONMEM、Monolix、Phoenix、Python、Rなど一般的に用いられる言語／ツールのいずれかの使用経験）
生体システムの数理モデルを用いた定量的解析を行った経験。特に、神経疾患領域にモデリング＆シミュレーションアプローチを適用した経験、もしくはその分野への強い関心があることが望ましい
複雑な情報を解析し、重要な科学的問いを特定できる優れた分析能力
複雑な数理モデル解析の結果を、クロスファンクショナルなチームメンバーに対して、分かりやすく簡潔に伝えるコミュニケーション能力
グローバルチームの下で業務を推進していくための、読み書き及び会話の両面での良好なビジネス英語力（TOEICスコア750点以上など）
MS/PhD/PharmD in chemical or biomedical engineering, pharmaceutical sciences, mathematics, physics, or equivalent area.
Strong competency in building mathematical models is required (in commonly used languages such as MATLAB, SimBiology, NONMEM, Monolix, Phoenix, Python, or R)
Experience in mathematical modeling of biological systems. Especially, an experience and/or interest in applying modeling and simulation approaches to neurological diseases is preferred.
Demonstrated strong analytical skills to evaluate complex information and identify key scientific questions.
Ability to communicate complex modeling results clearly and concisely to cross-functional audience is critical.
Good English communication skill in both written and verbal (TOEIC score ≥750, etc.) to work under global team setting
従業員数
5,486名
（単体 (連結 49,095名) ※2023年3月末時点）
勤務地
神奈川県
想定年収
800 万円 ~ 1,500 万円
従業員数
5,486名
（単体 (連結 49,095名) ※2023年3月末時点）
仕事内容
Job Description
”Better Health for People, Brighter Future for the World” is the purpose of a company. We aim to create a diverse and inclusive organization where people can thrive, grow and realize their own potential while enabling our purpose. We continue to innovate and drive changes that will transform the lives of patients. We’re looking for like-minded professionals to join us.
Takeda is a global values-based, R&D-driven biopharmaceutical leader. We are guided by our values of Takeda-ism, which has been passed down since the company’s founding. Takeda-ism incorporates Integrity, Fairness, Honesty, and Perseverance, with Integrity at the core. They are brought to life through actions based on Patient-Trust-Reputation-Business, in this order.
・Provide statistical support for Takeda preclinical campaigns for design and analysis in the discovery and development of targets and molecules for one or more disease areas.
・Collaborate with Computational Biology, Pharmacokinetics, and Safety scientists to explore methods and implement discovery strategies to enable data-driven decision making.
・Apply frequentist, Bayesian, ML/AI fit-for-purpose statistical analyses across various projects and data types.
・Serve as an expert and mentor in Quantitative Sciences group within implementing statistical development strategies using statistics and cross-disciplinary integrative data analytics.
Accountabilities:
・Lead implementation of SQS strategies and ensure deliverables by representing data science function on project teams in support of preclinical studies throughout the drug discovery units and supporting functions.
・Perform end-to-end data analyses, from hypotheses formulation, experimental design, writing analysis plans, data cleaning, executing analysis, and preparing reports and documentation.
・Strengthen Takeda’s advanced analytics toolkit by identifying, promoting, and applying emerging techniques, as well as by developing novel analysis tools as needed.
・Collaborate effectively within a matrix environment, working with scientists across various areas to understand the problems in terms of its chemistry, biology, and/or physical natures and to tailor data analyses to program-specific needs.
・Work closely with Takeda statisticians to ensure statistical issues in data analysis are addressed.
・Communicate internal and external resource and quality issues that may impact deliverables or timelines of the program. Escalate issues to management as appropriate in a timely manner.
・Respond to regulatory questions that are statistical in nature.
・Increase the external recognition of Takeda’s data science work by participating in conferences, publishing work and developing external collaborations.
”Better Health for People, Brighter Future for the World” is the purpose of a company. We aim to create a diverse and inclusive organization where people can thrive, grow and realize their own potential while enabling our purpose. We continue to innovate and drive changes that will transform the lives of patients. We’re looking for like-minded professionals to join us.
Takeda is a global values-based, R&D-driven biopharmaceutical leader. We are guided by our values of Takeda-ism, which has been passed down since the company’s founding. Takeda-ism incorporates Integrity, Fairness, Honesty, and Perseverance, with Integrity at the core. They are brought to life through actions based on Patient-Trust-Reputation-Business, in this order.
・Provide statistical support for Takeda preclinical campaigns for design and analysis in the discovery and development of targets and molecules for one or more disease areas.
・Collaborate with Computational Biology, Pharmacokinetics, and Safety scientists to explore methods and implement discovery strategies to enable data-driven decision making.
・Apply frequentist, Bayesian, ML/AI fit-for-purpose statistical analyses across various projects and data types.
・Serve as an expert and mentor in Quantitative Sciences group within implementing statistical development strategies using statistics and cross-disciplinary integrative data analytics.
Accountabilities:
・Lead implementation of SQS strategies and ensure deliverables by representing data science function on project teams in support of preclinical studies throughout the drug discovery units and supporting functions.
・Perform end-to-end data analyses, from hypotheses formulation, experimental design, writing analysis plans, data cleaning, executing analysis, and preparing reports and documentation.
・Strengthen Takeda’s advanced analytics toolkit by identifying, promoting, and applying emerging techniques, as well as by developing novel analysis tools as needed.
・Collaborate effectively within a matrix environment, working with scientists across various areas to understand the problems in terms of its chemistry, biology, and/or physical natures and to tailor data analyses to program-specific needs.
・Work closely with Takeda statisticians to ensure statistical issues in data analysis are addressed.
・Communicate internal and external resource and quality issues that may impact deliverables or timelines of the program. Escalate issues to management as appropriate in a timely manner.
・Respond to regulatory questions that are statistical in nature.
・Increase the external recognition of Takeda’s data science work by participating in conferences, publishing work and developing external collaborations.
求める経験 / スキル
Requirements:
Master’s degree or higher in statistics or related field
Good English communication skill in both written and verbal
High level of knowledge, expertise, and experience in biostatistics
High capacity for collecting information
Expert-level knowledge of data science programming languages (SAS, R, Python, or similar) and experience with recommended software development practices
Ability to work independently on complicated datasets, covering all aspects of data analysis
High level of expertise and experience in the pharmaceutical industry
Ability to judge regulatory risk and feasibility
Capacity to build statistical strategies for non-clinical work with fresh perspectives
Preparation for future business domains, such as AI/ML and Real-World Data
Strong communication and negotiation skills to lead non-clinical projects
Master’s degree or higher in statistics or related field
Good English communication skill in both written and verbal
High level of knowledge, expertise, and experience in biostatistics
High capacity for collecting information
Expert-level knowledge of data science programming languages (SAS, R, Python, or similar) and experience with recommended software development practices
Ability to work independently on complicated datasets, covering all aspects of data analysis
High level of expertise and experience in the pharmaceutical industry
Ability to judge regulatory risk and feasibility
Capacity to build statistical strategies for non-clinical work with fresh perspectives
Preparation for future business domains, such as AI/ML and Real-World Data
Strong communication and negotiation skills to lead non-clinical projects
従業員数
5,486名
（単体 (連結 49,095名) ※2023年3月末時点）
勤務地
神奈川県
想定年収
1,150 万円 ~ 1,600 万円
従業員数
5,486名
（単体 (連結 49,095名) ※2023年3月末時点）
仕事内容
■ 職務内容 / Job Description
A lead statistician (STAT) is a key player of conducting Real World Data (RWD) analysis of AZ KK so that those scientific values are enhanced. Therefore, STAT surely has the following responsibilities:
・Lead AZSS and Post marketing database (DB) research from a statistical point of view including research design, statistical analysis, and sample size calculation in collaboration with Data Scientist (DS).
・Assess study outcomes/study design/results, interpret research results and make descriptions with statistical insights (all Real World Data analyses including Market/R&D requests)
・Implement innovative methodology such as prediction or causality
・Use AI for automating regular tasks・Look for statistical topics related to observational/database research, do researches, and make manuscripts
STAT directly reports to the Director of Data Science.
A lead statistician (STAT) is a key player of conducting Real World Data (RWD) analysis of AZ KK so that those scientific values are enhanced. Therefore, STAT surely has the following responsibilities:
・Lead AZSS and Post marketing database (DB) research from a statistical point of view including research design, statistical analysis, and sample size calculation in collaboration with Data Scientist (DS).
・Assess study outcomes/study design/results, interpret research results and make descriptions with statistical insights (all Real World Data analyses including Market/R&D requests)
・Implement innovative methodology such as prediction or causality
・Use AI for automating regular tasks・Look for statistical topics related to observational/database research, do researches, and make manuscripts
STAT directly reports to the Director of Data Science.
求める経験 / スキル
■ 応募資格(経験、資格等) / Qualification (Experience & Skill etc.)
【経験 / Experience】
＜必須 / Mandatory＞
・Plan study design, sample size calculation, analysis in clinical trials or DB researches
・Statistician/Statistical programming in clinical development or DB researches
・Research for statistical methodology
・Make a publication (presentation at Academic association meetings/manuscripts)
＜歓迎 / Nice to have＞
・Experience in reviewing, assessing and using Real-World data for the research purposes to address clinical / research questions
・Networking, integrating and using EMR(electronic medical records)/EHR(electronic health record) data for the clinical / epidemiological research
・Using / applying bioinformatics methodologies to analyze medical big data / database / scientific research outcomes
・Health Technology Assessment in building models, estimating Health Care resources, analysing the health economics/technology and crafting value propositions
【資格 / License】
＜必須 / Mandatory＞
・Master degree in Statistics, Engineering, Science (Math, Physics, Iinformatics) or equivalent (MD/Public health/pharmaceutical science degree may be acceptable)
・Professional of statistics
＜歓迎 / Nice to have＞
・PhD in Biostatistics
【能力 / Skill-set】
＜必須 / Mandatory＞
・Programming skill of R, & SAS in clinical study/DB research
・Implementation of new technology & methodology
・Publication/Medical writing of own research
・Exchange of insights about statistical subjects with external
・Presentation at meetings about study design, results, and statistical methodology
＜歓迎 / Nice to have＞
・ Programming skill of Python
・Lead meeting of which agenda includes statistical topics
【語学 / Language】
＜必須 / Mandatory＞
・Read/write statistical documents including study population in English/Japanese
・Communicate, and discuss Statistics/bioinformatics topics with the key stakeholders and experts in English/Japanese practically
・Make a English presentation, organize and facilitate the research/clinical study in the global meetings
【その他 / Others】
＜必須 / Mandatory＞
Skill/knowledge
・Interpretation of analysis results and present external members at the Academic conference/decision making meetings
・Innovative methodology for analysis (e.g. Machine learning & Neural network)
【経験 / Experience】
＜必須 / Mandatory＞
・Plan study design, sample size calculation, analysis in clinical trials or DB researches
・Statistician/Statistical programming in clinical development or DB researches
・Research for statistical methodology
・Make a publication (presentation at Academic association meetings/manuscripts)
＜歓迎 / Nice to have＞
・Experience in reviewing, assessing and using Real-World data for the research purposes to address clinical / research questions
・Networking, integrating and using EMR(electronic medical records)/EHR(electronic health record) data for the clinical / epidemiological research
・Using / applying bioinformatics methodologies to analyze medical big data / database / scientific research outcomes
・Health Technology Assessment in building models, estimating Health Care resources, analysing the health economics/technology and crafting value propositions
【資格 / License】
＜必須 / Mandatory＞
・Master degree in Statistics, Engineering, Science (Math, Physics, Iinformatics) or equivalent (MD/Public health/pharmaceutical science degree may be acceptable)
・Professional of statistics
＜歓迎 / Nice to have＞
・PhD in Biostatistics
【能力 / Skill-set】
＜必須 / Mandatory＞
・Programming skill of R, & SAS in clinical study/DB research
・Implementation of new technology & methodology
・Publication/Medical writing of own research
・Exchange of insights about statistical subjects with external
・Presentation at meetings about study design, results, and statistical methodology
＜歓迎 / Nice to have＞
・ Programming skill of Python
・Lead meeting of which agenda includes statistical topics
【語学 / Language】
＜必須 / Mandatory＞
・Read/write statistical documents including study population in English/Japanese
・Communicate, and discuss Statistics/bioinformatics topics with the key stakeholders and experts in English/Japanese practically
・Make a English presentation, organize and facilitate the research/clinical study in the global meetings
【その他 / Others】
＜必須 / Mandatory＞
Skill/knowledge
・Interpretation of analysis results and present external members at the Academic conference/decision making meetings
・Innovative methodology for analysis (e.g. Machine learning & Neural network)
勤務地
複数あり
想定年収
1,100 万円 ~ 1,400 万円
仕事内容
■ 職務内容 / Job Description
A lead Data Scientist (DS) is an expert role in Real World Data(RWD) analysis to provide scientific expertise in evidence generation so that key research questions are sufficiently addressed and set target population for research. And all researches/analyses are planned and delivered in a way that represent cutting-edge science, methodologies, technologies, processes, and solutions in the Pharm industry. Lead Data Scientist reports to director of Data Science, Medical.
・Lead/co-lead observational/database research and data analysis including Market/R&D analysis
・Assess study design/target population/data source/data handling/analytical method and give clear inputs from an epidemiological point of view
・Oversee venders and manage timeline, quality of outputs, resource, & cost of their responsible researches
・Survey & assess the necessary information for database and recommend database that fits for research/analytical purpose
・Develop AI use fit for purpose
・Implement AI (including Generative AI) to their work process not only for simplifying DS regular tasks but also for advancing them
・Support for PARCS led by Pharmacovigilance department
A lead Data Scientist (DS) is an expert role in Real World Data(RWD) analysis to provide scientific expertise in evidence generation so that key research questions are sufficiently addressed and set target population for research. And all researches/analyses are planned and delivered in a way that represent cutting-edge science, methodologies, technologies, processes, and solutions in the Pharm industry. Lead Data Scientist reports to director of Data Science, Medical.
・Lead/co-lead observational/database research and data analysis including Market/R&D analysis
・Assess study design/target population/data source/data handling/analytical method and give clear inputs from an epidemiological point of view
・Oversee venders and manage timeline, quality of outputs, resource, & cost of their responsible researches
・Survey & assess the necessary information for database and recommend database that fits for research/analytical purpose
・Develop AI use fit for purpose
・Implement AI (including Generative AI) to their work process not only for simplifying DS regular tasks but also for advancing them
・Support for PARCS led by Pharmacovigilance department
求める経験 / スキル
【経験 / Experience】
＜必須 / Mandatory＞
・Design, analyze, interpret and publish researches for Data Science/Epidemiology/Clinical/Statistics
・Manage, and/or lead group of members who are responsible for conducting clinical/epidemiologic research, analysis of data, reading of the data for efficacy, safety, clinical effectiveness and epidemiological assessments (acceptable even if the leadership is primarily focused on the scientific features)
・Make manuscript for their own specialized topics
＜歓迎 / Nice to have＞
・Reviewing, assessing and using Real-World Data for research purposes to address clinical/research questions
・Networking, integrating and using EMR(electronic medical records)/EHR(electronic health record) data for clinical /epidemiological research
・Using/applying bioinformatic methodologies to analyze medical data/database/scientific research
【資格 / License】
＜必須 / Mandatory＞
・Master’s degree in public health or equivalent (individuals holding Data Science/Engineering/Pharmaceutical science/biostatistics degree are acceptable, but should have had the sufficient experience specialized in clinical development/epidemiological research)
＜歓迎 / Nice to have＞
・PhD in Data Science/Engineering/Pharmaceutical science/biostatistics or MD degree is desirable
【能力 / Skill-set】
＜必須 / Mandatory＞
・Apply appropriate study design & analytical methods to observational / Epidemiological / pragmatic interventional studies to combine business and scientific agenda
・Lead the interpretation of the scientific data, the translation to the appropriate messaging and drafting manuscript of relevant scientific publications
・Take a leadership in analyzing medical evidence gap, spotting opportunities/requirements for evidence generation and integrate them into a clear evidence plan/option in the cross-functional team
・Assess scientific feasibility in using/integrating databases for the research purposes
・Develop AI for making efficient way for daily work
・Manage project in planning, execution, and assessment, and apply the tools/frameworks/concepts to drive the effectiveness/performance of project teams
・Solid communication and interpersonal skills to enable effective leadership, coaching and collaborations
＜歓迎 / Nice to have＞
・Develop prompt of AI to get accurate answers
・Apply health technology assessments to make clear drug characteristics
【語学 / Language】
＜必須 / Mandatory＞
日本語 Japanese：
・Read/write scientific documents including data speculation in Japanese
・Communicate/discuss IT/bioinformatics topics with the key stakeholders and experts in Japanese practically
英語 English：
Read/write scientific documents including data speculation in English
・Communicate, and discuss IT/bioinformatics topics with the key stakeholders and experts in English practically
・Make a English presentation leading and facilitating research discussions in the global meetings
【その他 / Others】
＜必須 / Mandatory＞
・Make training plan about applications
・Harmonize process with global
・Communicate with external experts to search for suitable computer environment in AZ KK
・Learn new methodology and knowledge with respect to machine learning and neural network
＜必須 / Mandatory＞
・Design, analyze, interpret and publish researches for Data Science/Epidemiology/Clinical/Statistics
・Manage, and/or lead group of members who are responsible for conducting clinical/epidemiologic research, analysis of data, reading of the data for efficacy, safety, clinical effectiveness and epidemiological assessments (acceptable even if the leadership is primarily focused on the scientific features)
・Make manuscript for their own specialized topics
＜歓迎 / Nice to have＞
・Reviewing, assessing and using Real-World Data for research purposes to address clinical/research questions
・Networking, integrating and using EMR(electronic medical records)/EHR(electronic health record) data for clinical /epidemiological research
・Using/applying bioinformatic methodologies to analyze medical data/database/scientific research
【資格 / License】
＜必須 / Mandatory＞
・Master’s degree in public health or equivalent (individuals holding Data Science/Engineering/Pharmaceutical science/biostatistics degree are acceptable, but should have had the sufficient experience specialized in clinical development/epidemiological research)
＜歓迎 / Nice to have＞
・PhD in Data Science/Engineering/Pharmaceutical science/biostatistics or MD degree is desirable
【能力 / Skill-set】
＜必須 / Mandatory＞
・Apply appropriate study design & analytical methods to observational / Epidemiological / pragmatic interventional studies to combine business and scientific agenda
・Lead the interpretation of the scientific data, the translation to the appropriate messaging and drafting manuscript of relevant scientific publications
・Take a leadership in analyzing medical evidence gap, spotting opportunities/requirements for evidence generation and integrate them into a clear evidence plan/option in the cross-functional team
・Assess scientific feasibility in using/integrating databases for the research purposes
・Develop AI for making efficient way for daily work
・Manage project in planning, execution, and assessment, and apply the tools/frameworks/concepts to drive the effectiveness/performance of project teams
・Solid communication and interpersonal skills to enable effective leadership, coaching and collaborations
＜歓迎 / Nice to have＞
・Develop prompt of AI to get accurate answers
・Apply health technology assessments to make clear drug characteristics
【語学 / Language】
＜必須 / Mandatory＞
日本語 Japanese：
・Read/write scientific documents including data speculation in Japanese
・Communicate/discuss IT/bioinformatics topics with the key stakeholders and experts in Japanese practically
英語 English：
Read/write scientific documents including data speculation in English
・Communicate, and discuss IT/bioinformatics topics with the key stakeholders and experts in English practically
・Make a English presentation leading and facilitating research discussions in the global meetings
【その他 / Others】
＜必須 / Mandatory＞
・Make training plan about applications
・Harmonize process with global
・Communicate with external experts to search for suitable computer environment in AZ KK
・Learn new methodology and knowledge with respect to machine learning and neural network
勤務地
複数あり
想定年収
1,100 万円 ~ 1,400 万円
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職種から求人を探す
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業種から求人を探す
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勤務地から求人を探す
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年収から求人を探す
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